Energy-Efficient Networking Solutions in Cloud-Based Environments: A Systematic Literature Review
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paper_title: Exploring Power-Efficient Provisioning for Online Virtual Network Requests

paper_content:

In the paradigm of cloud computing, multiple users can share the cloud infrastructure resources. The application or service requests from a user can be abstracted as a virtual network (VN) request and submitted to the cloud-based data centers. How to map a virtual network onto the cloud infrastructure network is a challenging issue in cloud resource provisioning. Current researches about virtual network mapping problem mainly focus on resource efficiency, which can be classified into resource efficient VN mapping or cost efficient VN mapping. However, the amount of power or energy consumed by data centers takes a large part of all of the power consumption. This may not only leads to a higher expenditure on the operation of data centers but also contribute to carbon emissions and the greenhouse effect. In this work we study the problem of power efficient virtual network mapping and propose a framework and algorithm for solving this problem. The simulation results show that our approach performs well.
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paper_title: ElasticTree: Saving Energy in Data Center Networks

paper_content:

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
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paper_title: Systematic literature reviews in software engineering – A systematic literature review

paper_content:

Background: In 2004 the concept of evidence-based software engineering (EBSE) was introduced at the ICSE04 conference. Aims: This study assesses the impact of systematic literature reviews (SLRs) which are the recommended EBSE method for aggregating evidence. Method: We used the standard systematic literature review method employing a manual search of 10 journals and 4 conference proceedings. Results: Of 20 relevant studies, eight addressed research trends rather than technique evaluation. Seven SLRs addressed cost estimation. The quality of SLRs was fair with only three scoring less than 2 out of 4. Conclusions: Currently, the topic areas covered by SLRs are limited. European researchers, particularly those at the Simula Laboratory appear to be the leading exponents of systematic literature reviews. The series of cost estimation SLRs demonstrate the potential value of EBSE for synthesising evidence and making it available to practitioners.
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paper_title: DENS: data center energy-efficient network-aware scheduling

paper_content:

In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The existing work in data center energy optimization is focusing only on job distribution between computing servers based on workload or thermal profiles. This paper underlines the role of communication fabric in data center energy consumption and presents a scheduling approach that combines energy efficiency and network awareness, named DENS. The DENS methodology balances the energy consumption of a data center, individual job performance, and traffic demands. The proposed approach optimizes the tradeoff between job consolidation (to minimize the amount of computing servers) and distribution of traffic patterns (to avoid hotspots in the data center network).
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paper_title: Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport

paper_content:

Network-based cloud computing is rapidly expanding as an alternative to conventional office-based computing. As cloud computing becomes more widespread, the energy consumption of the network and computing resources that underpin the cloud will grow. This is happening at a time when there is increasing attention being paid to the need to manage energy consumption across the entire information and communications technology (ICT) sector. While data center energy use has received much attention recently, there has been less attention paid to the energy consumption of the transmission and switching networks that are key to connecting users to the cloud. In this paper, we present an analysis of energy consumption in cloud computing. The analysis considers both public and private clouds, and includes energy consumption in switching and transmission as well as data processing and data storage. We show that energy consumption in transport and switching can be a significant percentage of total energy consumption in cloud computing. Cloud computing can enable more energy-efficient use of computing power, especially when the computing tasks are of low intensity or infrequent. However, under some circum- stances cloud computing can consume more energy than conventional computing where each user performs all com- puting on their own personal computer (PC).
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paper_title: A survey on energy and power consumption models for Greener Cloud

paper_content:

The growing demand of computation, large data storage needed for running a high performance computing enterprise and high dimensional data based web application increases the energy and power consumed by large infrastructure. Cloud computing is providing a solution as part of the Green IT initiative to reduce the adverse environmental impacts and save energy. Our paper describes important metrics of cloud computing which makes it greener. We discuss the various power and energy models and identify major challenges to build a model for Green Cloud. We also discuss the ways to reduce power and energy in terms of cloud computing services. Our work surveys the various models and helps understand the road map for a greener cloud.
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paper_title: A survey of research on greening data centers

paper_content:

The growing economical and environmental cost of data centers due to the high energy consumption is becoming a major issue. “Green Data Centers” refers to, energy aware, energy efficient and CO2 emission minimizing designs, protocols, devices, infrastructures and algorithms for data centers. Today's data centers are provisioned for peak load. However, it is shown that servers are idle most of the time. Idle servers and the connected network elements are consuming considerable amount of energy. In this survey, we identify the key enablers of green data center research. Firstly we overview the green metrics that are applicable to data centers. Then we describe the most recent stage of research and give a taxonomy of the related work. We focus on computing and networking proposals for green data centers, even though we briefly describe some other green research related to data centers such as cloud computing, cooling.
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paper_title: Energy Efficiency in the Future Internet: A Survey of Existing Approaches and Trends in Energy-Aware Fixed Network Infrastructures

paper_content:

The concept of energy-efficient networking has begun to spread in the past few years, gaining increasing popularity. Besides the widespread sensitivity to ecological issues, such interest also stems from economic needs, since both energy costs and electrical requirements of telcos' and Internet Service Providers' infrastructures around the world show a continuously growing trend. In this respect, a common opinion among networking researchers is that the sole introduction of low consumption silicon technologies may not be enough to effectively curb energy requirements. Thus, for disruptively boosting the network energy efficiency, these hardware enhancements must be integrated with ad-hoc mechanisms that explicitly manage energy saving, by exploiting network-specific features. This paper aims at providing a twofold contribution to green networking. At first, we explore current perspectives in power consumption for next generation networks. Secondly, we provide a detailed survey on emerging technologies, projects, and work-in-progress standards, which can be adopted in networks and related infrastructures in order to reduce their carbon footprint. The considered approaches range from energy saving techniques for networked hosts, to technologies and mechanisms for designing next-generation and energy-aware networks and networking equipment.
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paper_title: A survey of energy-efficient techniques in cloud data centers

paper_content:

The fast growing number of data centers in cloud raises high energy consumption problem. Thus there is a need for “Greening” in data center. ”Greening” means applying energy-saving techniques and designs in data center for power saving. Although cloud data centers nowadays are over-provisioned for high load, however, it is shown that the average data center load is only 30% [1]. There is lack of resource allocation mechanisms in data centers that caused the above problem. In this article, we review the “green” strategies, which are applied in data center to reduce energy consumption. First, we give the overview of the green metrics for data centers. Then, we present the most recent research in this area and give taxonomy of the related work.
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paper_title: Energy Efficiency in Telecom Optical Networks

paper_content:

Since the energy crisis and environmental protection are gaining increasing concerns in recent years, new research topics to devise technological solutions for energy conservation are being investigated in many scientific disciplines. Specifically, due to the rapid growth of energy consumption in ICT (Information and Communication Technologies), lot of attention is being devoted towards "green" ICT solutions. In this paper, we provide a comprehensive survey of the most relevant research activities for minimizing energy consumption in telecom networks, with a specific emphasis on those employing optical technologies. We investigate the energy-minimization opportunities enabled by optical technologies and classify the existing approaches over different network domains, namely core, metro, and access networks. A section is also devoted to describe energy-efficient solutions for some of today's important applications using optical network technology, e.g., grid computing and data centers. We provide an overview of the ongoing standardization efforts in this area. This work presents a comprehensive and timely survey on a growing field of research, as it covers most aspects of energy consumption in optical telecom networks. We aim at providing a comprehensive reference for the growing base of researchers who will work on energy efficiency of telecom networks in the upcoming years.
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paper_title: A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems

paper_content:

Abstract Traditionally, the development of computing systems has been focused on performance improvements driven by the demand of applications from consumer, scientific, and business domains. However, the ever-increasing energy consumption of computing systems has started to limit further performance growth due to overwhelming electricity bills and carbon dioxide footprints. Therefore, the goal of the computer system design has been shifted to power and energy efficiency. To identify open challenges in the area and facilitate future advancements, it is essential to synthesize and classify the research on power- and energy-efficient design conducted to date. In this study, we discuss causes and problems of high power/energy consumption, and present a taxonomy of energy-efficient design of computing systems covering the hardware, operating system, virtualization, and data center levels. We survey various key works in the area and map them onto our taxonomy to guide future design and development efforts. This chapter concludes with a discussion on advancements identified in energy-efficient computing and our vision for future research directions.
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paper_title: Systematic literature reviews in software engineering – A systematic literature review

paper_content:

Background: In 2004 the concept of evidence-based software engineering (EBSE) was introduced at the ICSE04 conference. Aims: This study assesses the impact of systematic literature reviews (SLRs) which are the recommended EBSE method for aggregating evidence. Method: We used the standard systematic literature review method employing a manual search of 10 journals and 4 conference proceedings. Results: Of 20 relevant studies, eight addressed research trends rather than technique evaluation. Seven SLRs addressed cost estimation. The quality of SLRs was fair with only three scoring less than 2 out of 4. Conclusions: Currently, the topic areas covered by SLRs are limited. European researchers, particularly those at the Simula Laboratory appear to be the leading exponents of systematic literature reviews. The series of cost estimation SLRs demonstrate the potential value of EBSE for synthesising evidence and making it available to practitioners.
---
paper_title: Exploring Power-Efficient Provisioning for Online Virtual Network Requests

paper_content:

In the paradigm of cloud computing, multiple users can share the cloud infrastructure resources. The application or service requests from a user can be abstracted as a virtual network (VN) request and submitted to the cloud-based data centers. How to map a virtual network onto the cloud infrastructure network is a challenging issue in cloud resource provisioning. Current researches about virtual network mapping problem mainly focus on resource efficiency, which can be classified into resource efficient VN mapping or cost efficient VN mapping. However, the amount of power or energy consumed by data centers takes a large part of all of the power consumption. This may not only leads to a higher expenditure on the operation of data centers but also contribute to carbon emissions and the greenhouse effect. In this work we study the problem of power efficient virtual network mapping and propose a framework and algorithm for solving this problem. The simulation results show that our approach performs well.
---
paper_title: VMFlow: Leveraging VM Mobility to Reduce Network Power Costs in Data Centers

paper_content:

Networking costs play an important role in the overall costs of a modern data center. Network power, for example, has been estimated at 10-20% of the overall data center power consumption. Traditional power saving techniques in data centers focus on server power reduction through Virtual Machine (VM) migration and server consolidation, without taking into account the network topology and the current network traffic. On the other hand, recent techniques to save network power have not yet utilized the various degrees of freedom that current and future data centers will soon provide. These include VM migration capabilities across the entire data center network, on demand routing through programmable control planes, and high bisection bandwidth networks. ::: ::: This paper presents VMFlow: a framework for placement and migration of VMs that takes into account both the network topology as well as network traffic demands, to meet the objective of network power reduction while satisfying as many network demands as possible. We present network power aware VM placement and demand routing as an optimization problem. We show that the problem is NP-complete, and present a fast heuristic for the same. Next, we present the design of a simulator that implements this heuristic and simulates its executions over a data center network with a CLOS topology. Our simulation results using real data center traces demonstrate that, by applying an intelligent VM placement heuristic, VMFlow can achieve 15-20% additional savings in network power while satisfying 5-6 times more network demands as compared to recently proposed techniques for saving network power.
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paper_title: Network Element Scheduling for Achieving Energy-Aware Data Center Networks

paper_content:

The goal of data center network is to interconnect a massive number of servers so as to provide reliable and scalable computing and storage infrastructure for cloud-based Internet services and data-intensive scientific applications. Recent studies reveal that the network elements consume 10∼20% of the overall power in a data center, which has introduced a challenge to reducing network energy cost without adversely affecting network performance. Considering unique features of traffic patterns and network topologies in data centers, this paper proposes a novel Network Element Scheduling Scheme (NESS) to reduce data center energy consumption from the networking perspective. The core idea is to turn on only a minimal subset of network elements to satisfy routing requirements, and put to sleep or shut down the rest unneeded ones for energy saving. In NESS, the logical network architecture formed by the active elements not only achieves the basic purpose for server interconnections in data centers, but also can support multi-path routing between pairs of hot servers for load balancing. Simulation experiments are performed in representative data center network topologies, and the results demonstrate the effectiveness of NESS in energy conserving on network elements in data centers.
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paper_title: On the Complexity of Power Minimization Schemes in Data Center Networks

paper_content:

In this paper, we consider migration of virtual machines in a data center to minimize network power consumption. Network power is consumed when switches are turned on, and conserved when they are turned off; the optimization problem then is to site virtual machines within the data center to achieve connectivity and desired bandwidth while turning on as few switches as possible. Depending upon specifics of the permissible optimization, and topology considerations within the data center, this optimization problem can be easy, or hard. We fully taxonomize the suite of optimization problems in this general space, showing that the most complex problem (placement and routing of virtual machines in a topologically-rich data center network) is NP- hard. We offer a placement technique based on a classic VLSI placement algorithm, and demonstrate efficacy on a trace set derived from a production data center.
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paper_title: Energy-aware routing in data center network

paper_content:

The goal of data center network is to interconnect the massive number of data center servers, and provide efficient and fault-tolerant routing service to upper-layer applications. To overcome the problem of tree architecture in current practice, many new network architectures are proposed, represented by Fat-Tree, BCube, and etc. A consistent theme in these new architectures is that a large number of network devices are used to achieve 1:1 oversubscription ratio. However, at most time, data center traffic is far below the peak value. The idle network devices will waste significant amount of energy, which is now a headache for many data center owners. In this paper, we discuss how to save energy consumption in high-density data center networks in a routing perspective. We call this kind of routing energy-aware routing. The key idea is to use as few network devices to provide the routing service as possible, with no/little sacrifice on the network performance. Meanwhile, the idle network devices can be shutdown or put into sleep mode for energy saving. We establish the model of energy-aware routing in data center network, and design a heuristic algorithm to achieve the idea. Our simulation in typical data center networks shows that energy-aware routing can effectively save power consumed by network devices.
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paper_title: GreenVLAN: An energy-efficient approach for VLAN design

paper_content:

The greening of the Internet has become an important research issue due to the huge energy consumption of the Internet. In this paper, we explore network-level power saving mechanisms in the context of virtual local area networks (VLANs) given their importance and prevalence in enterprise, campus and Data Center Networks (DCNs). After investigating the disadvantages of current VLAN design method, we propose the GreenVLAN approach, which aims at reducing the power usage in the next generation Energy-Efficient Ethernet. The proposed GreenVLAN approach is formulated as a nonlinear integer programming problem with the total energy consumption as the objective to be minimized. Besides, we develop a practical heuristic algorithm to solve the proposed model and the complexity of the algorithm is analyzed. Our experiments on both simulated topology and real-world campus network demonstrate that Green-VLAN could achieve considerable power saving (reduce the power consumption of Ethernet links by about 27%∼53% for a typical VLAN configuration) compared with current VLAN practice.
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paper_title: ElasticTree: Saving Energy in Data Center Networks

paper_content:

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
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paper_title: Energy Aware Networked Cloud Mapping

paper_content:

Cloud computing has emerged as the computing paradigm that enables the delivery of utility-based IT services to users. The hyper-growth of Cloud computing has led to increased power consumption with significant consequences both in terms of environmental and operational costs. Hence, over the last years, attention has been drawn to optimizing energy consumption at the data center, aimed at the reduction of carbon footprints. However the world of Cloud Computing is constantly developing, with new concepts introduced while additional challenges arise. In this paper, a method for energy efficient resource allocation is proposed, in the context of a networked cloud environment. The method employs dynamic server consolidation by periodic VM migration. The approach is validated conducting performance evaluation via simulation, while it is compared against energy aware / non energy aware methods, using a set of both power indication and resource allocation metrics.
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paper_title: Energy models driven green routing for data centers

paper_content:

Energy consumption is becoming a serious issue for data centers. Minimizing the energy consumption of a data center is a complex problem. It consists of developing energy models for servers and network elements and investigating energy-aware (green) routing strategies using these models. In this paper, we adapt energy models for servers and network elements in a data center. The server energy model incorporates the impact of temperature and voltage of a server on its leakage energy. Using the server and network energy models, we propose a green routing scheme that minimizes the total combined energy consumption of servers and network elements in a data center under dynamic traffic. The proposed green routing scheme uses dynamic voltage scaling, rate adaptation, and anycast transmission for minimizing the total energy consumption. Extensive simulation results validate the effectiveness of the proposed green routing in minimizing the total energy consumption of a data center as compared to well-known existing approaches.
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paper_title: Energy Aware Network Operations

paper_content:

Networking devices today consume a non-trivial amount of energy and it has been shown that this energy consumption is largely independent of the load through the devices. With a strong need to curtail the rising operational costs of IT infrastructure, there is a tremendous opportunity for introducing energy awareness in the design and operation of enterprise and data center networks. We focus on these networks as they are under the control of a single administrative domain in which network-wide control can be consistently applied. In this paper, we describe and analyze three approaches to saving energy in single administrative domain networks, without significantly impacting the networks' ability to provide the expected levels of performance and availability. We also explore the trade-offs between conserving energy and meeting performance and availability requirements. We conduct an extensive case study of our algorithms by simulating a real Web 2.0 workload in a real data center network topology using power characterizations that we obtain from real network hardware. Our results indicate that for our workload and data center scenario, 16% power savings (with no performance penalty and small decrease in availability) can be obtained merely by appropriately adjusting the active network elements (links). Significant additional savings (up to 75%) can be obtained by incorporating network traffic management and server workload consolidation.
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paper_title: Calculating the Minimum Bounds of Energy Consumption for Cloud Networks

paper_content:

This paper is aiming at facilitating the energy-efficient operation of an integrated optical network and IT infrastructure. In this context we propose an energy-efficient routing algorithm for provisioning of IT services that originate from specific source sites and which need to be executed by suitable IT resources (e.g. data centers). The routing approach followed is anycast, since the requirement for the IT services is the delivery of results, while the exact location of the execution of the job can be freely chosen. In this scenario, energy efficiency is achieved by identifying the least energy consuming IT and network resources required to support the services, enabling the switching off of any unused network and IT resources. Our results show significant energy savings that can reach up to 55% compared to energy-unaware schemes, depending on the granularity with which a data center is able to switch on/off servers.
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paper_title: VMPlanner : Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers

paper_content:

In recent years, the power costs of cloud data centers have become a practical concern and have attracted significant attention from both industry and academia. Most of the early works on data center energy efficiency have focused on the biggest power consumers (i.e., computer servers and cooling systems), yet without taking the networking part into consideration. However, recent studies have revealed that the network elements consume 10-20% of the total power in the data center, which poses a great challenge to effectively reducing network power cost without adversely affecting overall network performance. Based on the analysis on topology characteristics and traffic patterns of data centers, this paper presents a novel approach, called VMPlanner, for network power reduction in the virtualization-based data centers. The basic idea of VMPlanner is to optimize both virtual machine placement and traffic flow routing so as to turn off as many unneeded network elements as possible for power saving. We formulate the optimization problem, analyze its hardness, and solve it by designing VMPlanner as a stepwise optimization approach with three approximation algorithms. VMPlanner is implemented and evaluated in a simulated environment with traffic traces collected from a data center test-bed, and the experiment results illustrate the efficacy and efficiency of this approach.
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paper_title: Reducing Total Power Consumption Method in Cloud Computing Environments

paper_content:

The widespread use of cloud computing services is expected to increase the power consumed by ICT equipment in cloud computing environments rapidly. This paper first identifies the need of the collaboration among servers, the communication network and the power network, in order to reduce the total power consumption by the entire ICT equipment in cloud computing environments. Five fundamental policies for the collaboration are proposed and the algorithm to realize each collaboration policy is outlined. Next, this paper proposes possible signaling sequences to exchange information on power consumption between network and servers, in order to realize the proposed collaboration policy. Then, in order to reduce the power consumption by the network, this paper proposes a method of estimating the volume of power consumption by all network devices simply and assigning it to an individual user.
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paper_title: A distributed energy saving approach for Ethernet switches in data centers

paper_content:

With popularity of data centers, energy efficiency of Ethernet switches in them is becoming a critical issue. Most existing energy saving approaches use a centralized methodology that assumes global knowledge of data center networks. Though these approaches can achieve nearly optimal energy saving for static traffic patterns, they are not suitable when the traffic patterns can change rapidly or the data centers have a large size. To overcome these limitations, this paper proposes a novel distributed approach called eAware that dynamically idles a port or a switch to save energy by examining the queue lengths and utilizations at switch ports. Through extensive simulations in ns-2, we compare eAware with an existing energy oblivious approach, showing that eAware can save 30%–50% on the total energy consumption by switches in data centers, and only increases the average end-to-end delay of packets by 3%–20% and the packet loss ratio by 0%–0.9%.
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paper_title: A Comparison Study of Energy Proportionality of Data Center Network Architectures

paper_content:

Today's data center networks consume a great amount of energy, which significantly aggravates the operational cost of data centers and the carbon footprint. It is an ideal objective for operators to make the power consumption of data center networks proportional to the amount of network loads they carry. To this end, many recent researches are focusing on two representative methods: device-level sleeping technology and network-wide energy aware routing. It is important for operators to understand what effects these energy conservation methods have on improving the network energy proportionality. In the paper, we make a comparison study on the energy proportionality of data center networks, based on regular routing and energy-aware routing. Specifically, we first choose several typical data center network architectures and equalize their network performance. Afterwards, we analyze the maximum power consumption of data center networks without using any energy conservation strategy, and compare their energy proportionality when employing the sleeping technology and energy-aware routing respectively.
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paper_title: PCube: Improving Power Efficiency in Data Center Networks

paper_content:

To alleviate the growing concern of energy waste in networked devices, we present PCube, a server-centric data center structure that conserves energy by varying bandwidth availability based on traffic demand. PCube not only supports a low-power mode for existing data centers offering full bisection bandwidth without hardware modification or re-wiring, but also provides an alternative for new data centers at a lower construction cost. The bandwidth demand could be dynamic and scalable in the optimal way when considering conserving the energy waste. To further reduce the cost, we take advantage of traffic locality, and propose Hybrid PCube, in order to offer different bandwidth to different servers. We use samples of traffic from a real-world production data center with full bisection bandwidth across thousands of servers, and evaluate our proposed algorithm using these collected samples. Our experimental results have shown convincing evidence that the proposed algorithm is able to substantially reduce energy costs incurred by networked devices in data centers.
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paper_title: Energy-Saving Virtual Machine Placement in Cloud Data Centers

paper_content:

In cloud data centers, different mapping relationships between virtual machines (VMs) and physical machines (PMs) cause different resource utilization, therefore, how to place VMs on PMs to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. The existing VM placement schemes are to optimize physical server resources utilization or network resources utilization, but few of them focuses on optimizing multiple resources utilization simultaneously. To address the issue, this paper proposes a VM placement scheme meeting multiple resource constraints, such as the physical server size (CPU, memory, storage, bandwidth, etc.) and network link capacity to improve resource utilization and reduce both the number of active physical servers and network elements so as to finally reduce energy consumption. Since VM placement problem is abstracted as a combination of bin packing problem and quadratic assignment problem, which is also known as a classic combinatorial optimization and NP-hard problem, we design a novel greedy algorithm by combining minimum cut with the best-fit, and the simulations show that our solution achieves better results.
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paper_title: Honeyguide: A VM migration-aware network topology for saving energy consumption in data center networks

paper_content:

Network elements consume 10–20% of the total power in data centers. Today's network elements are not energy-proportional and consume constant energy1 regardless of the traffic amounts. Thus, turning off unused network switches is the most efficient way of saving energy consumption of data center networks. This paper presents Honeyguide, an energy optimizer for data center networks that not only turns off inactive switches but also increases the number of inactive switches for energy-efficiency. To this end, Honeyguide combines two techniques: 1) virtual machine (VM) and traffic consolidation, and 2) a slight extension to existing tree-based topologies. Honeyguide has the following advantages. VM consolidation, which is gracefully combined with traffic consolidation, can handle severe requirements on fault tolerance. It can be introduced into existing data centers without replacing already-deployed tree-based topologies. Our simulation results demonstrate that Honeyguide can save more energy consumption of network elements than conventional VM migration schemes, and the savings are up to 7.8% in a fat tree with k = 12.
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paper_title: Network Element Scheduling for Achieving Energy-Aware Data Center Networks

paper_content:

The goal of data center network is to interconnect a massive number of servers so as to provide reliable and scalable computing and storage infrastructure for cloud-based Internet services and data-intensive scientific applications. Recent studies reveal that the network elements consume 10∼20% of the overall power in a data center, which has introduced a challenge to reducing network energy cost without adversely affecting network performance. Considering unique features of traffic patterns and network topologies in data centers, this paper proposes a novel Network Element Scheduling Scheme (NESS) to reduce data center energy consumption from the networking perspective. The core idea is to turn on only a minimal subset of network elements to satisfy routing requirements, and put to sleep or shut down the rest unneeded ones for energy saving. In NESS, the logical network architecture formed by the active elements not only achieves the basic purpose for server interconnections in data centers, but also can support multi-path routing between pairs of hot servers for load balancing. Simulation experiments are performed in representative data center network topologies, and the results demonstrate the effectiveness of NESS in energy conserving on network elements in data centers.
---
paper_title: ElasticTree: Saving Energy in Data Center Networks

paper_content:

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
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paper_title: A virtual network to achieve low energy consumption in optical large-scale datacenter

paper_content:

A data center network should provide communication with sufficiently large bandwidth and small delay between all servers. On the other hand, energy consumption of the data center network should be minimized. To satisfy all of the above requirements, in this paper, we introduce the virtual network configured over the data center network constructed of the optical cross connects (OXCs) and the electronic switches. We design the virtual network topology (VNT) so as to achieve sufficiently large bandwidth and small delay with small energy consumption. To calculate the suitable VNT in a short period, we propose the topology called Generalized Flattened Butterfly and a method to set the parameters so as to suit the current condition. In our evaluation, we clarify that our method achieves the sufficient bandwidth and the target maximum number of hops between top-of rack(ToR) switches with small energy consumption.
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paper_title: VMFlow: Leveraging VM Mobility to Reduce Network Power Costs in Data Centers

paper_content:

Networking costs play an important role in the overall costs of a modern data center. Network power, for example, has been estimated at 10-20% of the overall data center power consumption. Traditional power saving techniques in data centers focus on server power reduction through Virtual Machine (VM) migration and server consolidation, without taking into account the network topology and the current network traffic. On the other hand, recent techniques to save network power have not yet utilized the various degrees of freedom that current and future data centers will soon provide. These include VM migration capabilities across the entire data center network, on demand routing through programmable control planes, and high bisection bandwidth networks. ::: ::: This paper presents VMFlow: a framework for placement and migration of VMs that takes into account both the network topology as well as network traffic demands, to meet the objective of network power reduction while satisfying as many network demands as possible. We present network power aware VM placement and demand routing as an optimization problem. We show that the problem is NP-complete, and present a fast heuristic for the same. Next, we present the design of a simulator that implements this heuristic and simulates its executions over a data center network with a CLOS topology. Our simulation results using real data center traces demonstrate that, by applying an intelligent VM placement heuristic, VMFlow can achieve 15-20% additional savings in network power while satisfying 5-6 times more network demands as compared to recently proposed techniques for saving network power.
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paper_title: Network Element Scheduling for Achieving Energy-Aware Data Center Networks

paper_content:

The goal of data center network is to interconnect a massive number of servers so as to provide reliable and scalable computing and storage infrastructure for cloud-based Internet services and data-intensive scientific applications. Recent studies reveal that the network elements consume 10∼20% of the overall power in a data center, which has introduced a challenge to reducing network energy cost without adversely affecting network performance. Considering unique features of traffic patterns and network topologies in data centers, this paper proposes a novel Network Element Scheduling Scheme (NESS) to reduce data center energy consumption from the networking perspective. The core idea is to turn on only a minimal subset of network elements to satisfy routing requirements, and put to sleep or shut down the rest unneeded ones for energy saving. In NESS, the logical network architecture formed by the active elements not only achieves the basic purpose for server interconnections in data centers, but also can support multi-path routing between pairs of hot servers for load balancing. Simulation experiments are performed in representative data center network topologies, and the results demonstrate the effectiveness of NESS in energy conserving on network elements in data centers.
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paper_title: Energy efficient data center network based on a flexible bandwidth MIMO OFDM optical interconnect

paper_content:

Next generation data centers will have to face an increased amount of network traffic due to emerging applications such as cloud computing. Processing larger data volume leads to higher energy consumption, which in turn causes higher operation expense. Optical interconnects have gained attention recently as a promising solution due to its large bandwidth and high energy efficiency compared to the current networks based on commodity electrical switches. In this paper, we evaluate the energy efficiency of a novel data center network architecture based on optical multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology. By utilizing passive optical switch (cyclic arrayed waveguide grating) and parallel signal detection technology to detect multiple optical channels simultaneously with a single photodetector, this architecture offers high energy efficiency. The comparison with a reference design based on commodity electrical switches shows that the proposed architecture can reduce the power consumption and operation cost significantly while providing higher throughput.
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paper_title: Energy-efficient, high-performance optoelectronic packet switching for intra-data center network

paper_content:

An energy-efficient, high-performance optoelectronic packet switching for intra-data center (DC) network is presented, in which hybrid optoelectronic packet routers (HOERs) are interconnected with 100 Gbps (25 Gbps×4 wavelengths) links. A novel “Express path (ExP)” is introduced to enable the flow control. Packets, which are a part of a flow, can be bypassed the intermediate nodes and directly forwarded to the destination through the ExP. This bypass allows substantial offload packets from the HOERs, while, on the other hand, an individual packet is processed and forwarded by the HOERs. OpenFlow controls both the flows and virtual machines (VMs) of server cluster in a centralized fashion. As a consequence, drastic reduction of the power consumption as well as low latency will be demonstrated with all-out proposed efforts in the hardware and the smart networking.
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paper_title: On the Complexity of Power Minimization Schemes in Data Center Networks

paper_content:

In this paper, we consider migration of virtual machines in a data center to minimize network power consumption. Network power is consumed when switches are turned on, and conserved when they are turned off; the optimization problem then is to site virtual machines within the data center to achieve connectivity and desired bandwidth while turning on as few switches as possible. Depending upon specifics of the permissible optimization, and topology considerations within the data center, this optimization problem can be easy, or hard. We fully taxonomize the suite of optimization problems in this general space, showing that the most complex problem (placement and routing of virtual machines in a topologically-rich data center network) is NP- hard. We offer a placement technique based on a classic VLSI placement algorithm, and demonstrate efficacy on a trace set derived from a production data center.
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paper_title: Energy-aware routing in data center network

paper_content:

The goal of data center network is to interconnect the massive number of data center servers, and provide efficient and fault-tolerant routing service to upper-layer applications. To overcome the problem of tree architecture in current practice, many new network architectures are proposed, represented by Fat-Tree, BCube, and etc. A consistent theme in these new architectures is that a large number of network devices are used to achieve 1:1 oversubscription ratio. However, at most time, data center traffic is far below the peak value. The idle network devices will waste significant amount of energy, which is now a headache for many data center owners. In this paper, we discuss how to save energy consumption in high-density data center networks in a routing perspective. We call this kind of routing energy-aware routing. The key idea is to use as few network devices to provide the routing service as possible, with no/little sacrifice on the network performance. Meanwhile, the idle network devices can be shutdown or put into sleep mode for energy saving. We establish the model of energy-aware routing in data center network, and design a heuristic algorithm to achieve the idea. Our simulation in typical data center networks shows that energy-aware routing can effectively save power consumed by network devices.
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paper_title: GreenVLAN: An energy-efficient approach for VLAN design

paper_content:

The greening of the Internet has become an important research issue due to the huge energy consumption of the Internet. In this paper, we explore network-level power saving mechanisms in the context of virtual local area networks (VLANs) given their importance and prevalence in enterprise, campus and Data Center Networks (DCNs). After investigating the disadvantages of current VLAN design method, we propose the GreenVLAN approach, which aims at reducing the power usage in the next generation Energy-Efficient Ethernet. The proposed GreenVLAN approach is formulated as a nonlinear integer programming problem with the total energy consumption as the objective to be minimized. Besides, we develop a practical heuristic algorithm to solve the proposed model and the complexity of the algorithm is analyzed. Our experiments on both simulated topology and real-world campus network demonstrate that Green-VLAN could achieve considerable power saving (reduce the power consumption of Ethernet links by about 27%∼53% for a typical VLAN configuration) compared with current VLAN practice.
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paper_title: ElasticTree: Saving Energy in Data Center Networks

paper_content:

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
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paper_title: Energy Aware Networked Cloud Mapping

paper_content:

Cloud computing has emerged as the computing paradigm that enables the delivery of utility-based IT services to users. The hyper-growth of Cloud computing has led to increased power consumption with significant consequences both in terms of environmental and operational costs. Hence, over the last years, attention has been drawn to optimizing energy consumption at the data center, aimed at the reduction of carbon footprints. However the world of Cloud Computing is constantly developing, with new concepts introduced while additional challenges arise. In this paper, a method for energy efficient resource allocation is proposed, in the context of a networked cloud environment. The method employs dynamic server consolidation by periodic VM migration. The approach is validated conducting performance evaluation via simulation, while it is compared against energy aware / non energy aware methods, using a set of both power indication and resource allocation metrics.
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paper_title: Energy models driven green routing for data centers

paper_content:

Energy consumption is becoming a serious issue for data centers. Minimizing the energy consumption of a data center is a complex problem. It consists of developing energy models for servers and network elements and investigating energy-aware (green) routing strategies using these models. In this paper, we adapt energy models for servers and network elements in a data center. The server energy model incorporates the impact of temperature and voltage of a server on its leakage energy. Using the server and network energy models, we propose a green routing scheme that minimizes the total combined energy consumption of servers and network elements in a data center under dynamic traffic. The proposed green routing scheme uses dynamic voltage scaling, rate adaptation, and anycast transmission for minimizing the total energy consumption. Extensive simulation results validate the effectiveness of the proposed green routing in minimizing the total energy consumption of a data center as compared to well-known existing approaches.
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paper_title: An Energy Aware Network Management Approach Using Server Profiling in 'Green' Clouds

paper_content:

Clouds and data centres are significant consumers of power. There are however, opportunities for optimising carbon cost here as resource redundancy is provisioned extensively. Data centre resources, and subsequently clouds which support them, are traditionally organised into tiers; switch-off activity when managing redundant resources therefore occurs in an approach which exploits cost advantages associated with closing down entire network portions. We suggest however, an alternative approach to optimise cloud operation while maintaining application QoS: Simulation experiments identify that network operation can be optimised by selecting servers which process traffic at a rate that more closely matches the packet arrival rate, and resources which provision excessive capacity additional to that required may be powered off for improved efficiency. This recognises that there is a point in server speed at which performance is optimised, and operation which is greater than or less than this rate will not achieve optimisation. A series of policies have been defined in this work for integration into cloud management procedures; performance results from their implementation and evaluation in simulation show improved efficiency by selecting servers based on these relationships.
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paper_title: Energy Aware Network Operations

paper_content:

Networking devices today consume a non-trivial amount of energy and it has been shown that this energy consumption is largely independent of the load through the devices. With a strong need to curtail the rising operational costs of IT infrastructure, there is a tremendous opportunity for introducing energy awareness in the design and operation of enterprise and data center networks. We focus on these networks as they are under the control of a single administrative domain in which network-wide control can be consistently applied. In this paper, we describe and analyze three approaches to saving energy in single administrative domain networks, without significantly impacting the networks' ability to provide the expected levels of performance and availability. We also explore the trade-offs between conserving energy and meeting performance and availability requirements. We conduct an extensive case study of our algorithms by simulating a real Web 2.0 workload in a real data center network topology using power characterizations that we obtain from real network hardware. Our results indicate that for our workload and data center scenario, 16% power savings (with no performance penalty and small decrease in availability) can be obtained merely by appropriately adjusting the active network elements (links). Significant additional savings (up to 75%) can be obtained by incorporating network traffic management and server workload consolidation.
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paper_title: Design of energy-efficient cloud systems via network and resource virtualization

paper_content:

Data centers play a crucial role in the delivery of cloud services by enabling on-demand access to the shared resources such as software, platform and infrastructure. Virtual machine VM allocation is one of the challenging tasks in data center management since user requirements, typically expressed as service-level agreements, have to be met with the minimum operational expenditure. Despite their huge processing and storage facilities, data centers are among the major contributors to greenhouse gas emissions of IT services. In this paper, we propose a holistic approach for a large-scale cloud system where the cloud services are provisioned by several data centers interconnected over the backbone network. Leveraging the possibility to virtualize the backbone topology in order to bypass IP routers, which are major power consumers in the core network, we propose a mixed integer linear programming MILP formulation for VM placement that aims at minimizing both power consumption at the virtualized backbone network and resource usage inside data centers. Since the general holistic MILP formulation requires heavy and long-running computations, we partition the problem into two sub-problems, namely, intra and inter-data center VM placement. In addition, for the inter-data center VM placement, we also propose a heuristic to solve the virtualized backbone topology reconfiguration computation in reasonable time. We thoroughly assessed the performance of our proposed solution, comparing it with another notable MILP proposal in the literature; collected experimental results show the benefit of the proposed management scheme in terms of power consumption, resource utilization and fairness for medium size data centers. Copyright © 2013 John Wiley & Sons, Ltd.
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paper_title: VMPlanner : Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers

paper_content:

In recent years, the power costs of cloud data centers have become a practical concern and have attracted significant attention from both industry and academia. Most of the early works on data center energy efficiency have focused on the biggest power consumers (i.e., computer servers and cooling systems), yet without taking the networking part into consideration. However, recent studies have revealed that the network elements consume 10-20% of the total power in the data center, which poses a great challenge to effectively reducing network power cost without adversely affecting overall network performance. Based on the analysis on topology characteristics and traffic patterns of data centers, this paper presents a novel approach, called VMPlanner, for network power reduction in the virtualization-based data centers. The basic idea of VMPlanner is to optimize both virtual machine placement and traffic flow routing so as to turn off as many unneeded network elements as possible for power saving. We formulate the optimization problem, analyze its hardness, and solve it by designing VMPlanner as a stepwise optimization approach with three approximation algorithms. VMPlanner is implemented and evaluated in a simulated environment with traffic traces collected from a data center test-bed, and the experiment results illustrate the efficacy and efficiency of this approach.
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paper_title: Designing Energy-Efficient Data Center Networks Using Space-Time Optical Interconnection Architectures

paper_content:

This paper considers a space-time interconnection architecture (STIA) based on optical devices and proposes its introduction in data center networks. The power consumption of the STIA is modeled, accounting for the energy proportionality of the optical devices in the STIA. Using such a model, a STIA-based network is designed using three different topologies, tree, folded Clos, and flattened butterfly, and optimized for power efficiency. Results show that, for a fixed topology, small-size STIAs are an energy-efficient solution for data center networks and allow a power reduction of more than an order of magnitude with respect to the Ethernet-based network. The comparison for the same bisection bandwidth shows that folded Clos and flattened butterfly outperform tree, whose power consumption is strongly dependent on the oversubscription ratio selected.
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paper_title: How can architecture help to reduce energy consumption in data center networking

paper_content:

Reducing the power consumption of data centers has recently been received much attention from the research community and the industry alike. It is because the benefits are manifold: for the data centers themselves and towards the environment. A number of issues concerning with the consumption of the servers or the switches have been investigated. However, the energy requirement of the data center architecture has not yet been sufficiently addressed. In this paper, we address this issue and make two key contributions. Before delving into the details of possible solutions for reducing power of existing data center architectures, we first characterize the impact of architectural parameters on the power consumption of data centers by presenting preliminary results on the power consumption of state-of-the-art data center structures, namely BCube [8], DCell [9], and Fat-tree [1, 11, 7]. Secondly, based on the insights and lessons learnt from the analysis, we present our vision on possible practical solutions to reduce the energy usage of data center networking.
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paper_title: Energy-saving self-configuring networked data centers

paper_content:

In this paper, we develop the optimal minimum-energy scheduler for the dynamic online joint allocation of the task sizes, computing rates, communication rates and communication powers in virtualized Networked Data Centers (NetDCs) that operates under hard per-job delay-constraints. The referred NetDC's infrastructure is composed by multiple frequency-scalable Virtual Machines (VMs), that are interconnected by a bandwidth and power-limited switched Local Area Network (LAN). Due to the nonlinear power-vs.-communication rate relationship, the resulting Computing-Communication Optimization Problem (CCOP) is inherently nonconvex. In order to analytically compute the exact solution of the CCOP, we develop a solving approach that relies on the following two main steps: (i) we prove that the CCOP retains a loosely coupled structure, that allows us to perform the lossless decomposition of the CCOP into the cascade of two simpler sub-problems; and, (ii) we prove that the coupling between the aforementioned sub-problems is provided by a (scalar) constraint, that is linear in the offered workload. The resulting optimal scheduler is amenable of scalable and distributed online implementation and its analytical characterization is in closed-form. After numerically testing its actual performance under randomly time-varying synthetically generated and real-world measured workload traces, we compare the obtained performance with the corresponding ones of some state-of-the-art static and sequential schedulers.
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paper_title: Reducing Total Power Consumption Method in Cloud Computing Environments

paper_content:

The widespread use of cloud computing services is expected to increase the power consumed by ICT equipment in cloud computing environments rapidly. This paper first identifies the need of the collaboration among servers, the communication network and the power network, in order to reduce the total power consumption by the entire ICT equipment in cloud computing environments. Five fundamental policies for the collaboration are proposed and the algorithm to realize each collaboration policy is outlined. Next, this paper proposes possible signaling sequences to exchange information on power consumption between network and servers, in order to realize the proposed collaboration policy. Then, in order to reduce the power consumption by the network, this paper proposes a method of estimating the volume of power consumption by all network devices simply and assigning it to an individual user.
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paper_title: A distributed energy saving approach for Ethernet switches in data centers

paper_content:

With popularity of data centers, energy efficiency of Ethernet switches in them is becoming a critical issue. Most existing energy saving approaches use a centralized methodology that assumes global knowledge of data center networks. Though these approaches can achieve nearly optimal energy saving for static traffic patterns, they are not suitable when the traffic patterns can change rapidly or the data centers have a large size. To overcome these limitations, this paper proposes a novel distributed approach called eAware that dynamically idles a port or a switch to save energy by examining the queue lengths and utilizations at switch ports. Through extensive simulations in ns-2, we compare eAware with an existing energy oblivious approach, showing that eAware can save 30%–50% on the total energy consumption by switches in data centers, and only increases the average end-to-end delay of packets by 3%–20% and the packet loss ratio by 0%–0.9%.
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paper_title: A Comparison Study of Energy Proportionality of Data Center Network Architectures

paper_content:

Today's data center networks consume a great amount of energy, which significantly aggravates the operational cost of data centers and the carbon footprint. It is an ideal objective for operators to make the power consumption of data center networks proportional to the amount of network loads they carry. To this end, many recent researches are focusing on two representative methods: device-level sleeping technology and network-wide energy aware routing. It is important for operators to understand what effects these energy conservation methods have on improving the network energy proportionality. In the paper, we make a comparison study on the energy proportionality of data center networks, based on regular routing and energy-aware routing. Specifically, we first choose several typical data center network architectures and equalize their network performance. Afterwards, we analyze the maximum power consumption of data center networks without using any energy conservation strategy, and compare their energy proportionality when employing the sleeping technology and energy-aware routing respectively.
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paper_title: PCube: Improving Power Efficiency in Data Center Networks

paper_content:

To alleviate the growing concern of energy waste in networked devices, we present PCube, a server-centric data center structure that conserves energy by varying bandwidth availability based on traffic demand. PCube not only supports a low-power mode for existing data centers offering full bisection bandwidth without hardware modification or re-wiring, but also provides an alternative for new data centers at a lower construction cost. The bandwidth demand could be dynamic and scalable in the optimal way when considering conserving the energy waste. To further reduce the cost, we take advantage of traffic locality, and propose Hybrid PCube, in order to offer different bandwidth to different servers. We use samples of traffic from a real-world production data center with full bisection bandwidth across thousands of servers, and evaluate our proposed algorithm using these collected samples. Our experimental results have shown convincing evidence that the proposed algorithm is able to substantially reduce energy costs incurred by networked devices in data centers.
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paper_title: Enhancing data centre networking using energy aware optical interconnects

paper_content:

In a fast changing world where information technology drives economic prosperity, the number of data centres has grown significantly in the past few years. These data centres require large amount of energy in order to meet up with increasing demands. An overview of energy efficient optical interconnects as a means of reducing energy consumption without compromising speed and accuracy was presented. New methods by which energy efficiency can be achieved using OCDMA multiplexing techniques for future optical interconnections were discussed. We also presented some challenges that might inhibit effective implementation of the OCDMA multiplexing scheme.
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paper_title: A virtual network to achieve low energy consumption in optical large-scale datacenter

paper_content:

A data center network should provide communication with sufficiently large bandwidth and small delay between all servers. On the other hand, energy consumption of the data center network should be minimized. To satisfy all of the above requirements, in this paper, we introduce the virtual network configured over the data center network constructed of the optical cross connects (OXCs) and the electronic switches. We design the virtual network topology (VNT) so as to achieve sufficiently large bandwidth and small delay with small energy consumption. To calculate the suitable VNT in a short period, we propose the topology called Generalized Flattened Butterfly and a method to set the parameters so as to suit the current condition. In our evaluation, we clarify that our method achieves the sufficient bandwidth and the target maximum number of hops between top-of rack(ToR) switches with small energy consumption.
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paper_title: Energy-Saving Virtual Machine Placement in Cloud Data Centers

paper_content:

In cloud data centers, different mapping relationships between virtual machines (VMs) and physical machines (PMs) cause different resource utilization, therefore, how to place VMs on PMs to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. The existing VM placement schemes are to optimize physical server resources utilization or network resources utilization, but few of them focuses on optimizing multiple resources utilization simultaneously. To address the issue, this paper proposes a VM placement scheme meeting multiple resource constraints, such as the physical server size (CPU, memory, storage, bandwidth, etc.) and network link capacity to improve resource utilization and reduce both the number of active physical servers and network elements so as to finally reduce energy consumption. Since VM placement problem is abstracted as a combination of bin packing problem and quadratic assignment problem, which is also known as a classic combinatorial optimization and NP-hard problem, we design a novel greedy algorithm by combining minimum cut with the best-fit, and the simulations show that our solution achieves better results.
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paper_title: Honeyguide: A VM migration-aware network topology for saving energy consumption in data center networks

paper_content:

Network elements consume 10–20% of the total power in data centers. Today's network elements are not energy-proportional and consume constant energy1 regardless of the traffic amounts. Thus, turning off unused network switches is the most efficient way of saving energy consumption of data center networks. This paper presents Honeyguide, an energy optimizer for data center networks that not only turns off inactive switches but also increases the number of inactive switches for energy-efficiency. To this end, Honeyguide combines two techniques: 1) virtual machine (VM) and traffic consolidation, and 2) a slight extension to existing tree-based topologies. Honeyguide has the following advantages. VM consolidation, which is gracefully combined with traffic consolidation, can handle severe requirements on fault tolerance. It can be introduced into existing data centers without replacing already-deployed tree-based topologies. Our simulation results demonstrate that Honeyguide can save more energy consumption of network elements than conventional VM migration schemes, and the savings are up to 7.8% in a fat tree with k = 12.
---
paper_title: Designing Energy-Efficient Data Center Networks Using Space-Time Optical Interconnection Architectures

paper_content:

This paper considers a space-time interconnection architecture (STIA) based on optical devices and proposes its introduction in data center networks. The power consumption of the STIA is modeled, accounting for the energy proportionality of the optical devices in the STIA. Using such a model, a STIA-based network is designed using three different topologies, tree, folded Clos, and flattened butterfly, and optimized for power efficiency. Results show that, for a fixed topology, small-size STIAs are an energy-efficient solution for data center networks and allow a power reduction of more than an order of magnitude with respect to the Ethernet-based network. The comparison for the same bisection bandwidth shows that folded Clos and flattened butterfly outperform tree, whose power consumption is strongly dependent on the oversubscription ratio selected.
---
paper_title: Network Element Scheduling for Achieving Energy-Aware Data Center Networks

paper_content:

The goal of data center network is to interconnect a massive number of servers so as to provide reliable and scalable computing and storage infrastructure for cloud-based Internet services and data-intensive scientific applications. Recent studies reveal that the network elements consume 10∼20% of the overall power in a data center, which has introduced a challenge to reducing network energy cost without adversely affecting network performance. Considering unique features of traffic patterns and network topologies in data centers, this paper proposes a novel Network Element Scheduling Scheme (NESS) to reduce data center energy consumption from the networking perspective. The core idea is to turn on only a minimal subset of network elements to satisfy routing requirements, and put to sleep or shut down the rest unneeded ones for energy saving. In NESS, the logical network architecture formed by the active elements not only achieves the basic purpose for server interconnections in data centers, but also can support multi-path routing between pairs of hot servers for load balancing. Simulation experiments are performed in representative data center network topologies, and the results demonstrate the effectiveness of NESS in energy conserving on network elements in data centers.
---
paper_title: Energy-aware routing in data center network

paper_content:

The goal of data center network is to interconnect the massive number of data center servers, and provide efficient and fault-tolerant routing service to upper-layer applications. To overcome the problem of tree architecture in current practice, many new network architectures are proposed, represented by Fat-Tree, BCube, and etc. A consistent theme in these new architectures is that a large number of network devices are used to achieve 1:1 oversubscription ratio. However, at most time, data center traffic is far below the peak value. The idle network devices will waste significant amount of energy, which is now a headache for many data center owners. In this paper, we discuss how to save energy consumption in high-density data center networks in a routing perspective. We call this kind of routing energy-aware routing. The key idea is to use as few network devices to provide the routing service as possible, with no/little sacrifice on the network performance. Meanwhile, the idle network devices can be shutdown or put into sleep mode for energy saving. We establish the model of energy-aware routing in data center network, and design a heuristic algorithm to achieve the idea. Our simulation in typical data center networks shows that energy-aware routing can effectively save power consumed by network devices.
---
paper_title: VMFlow: Leveraging VM Mobility to Reduce Network Power Costs in Data Centers

paper_content:

Networking costs play an important role in the overall costs of a modern data center. Network power, for example, has been estimated at 10-20% of the overall data center power consumption. Traditional power saving techniques in data centers focus on server power reduction through Virtual Machine (VM) migration and server consolidation, without taking into account the network topology and the current network traffic. On the other hand, recent techniques to save network power have not yet utilized the various degrees of freedom that current and future data centers will soon provide. These include VM migration capabilities across the entire data center network, on demand routing through programmable control planes, and high bisection bandwidth networks. ::: ::: This paper presents VMFlow: a framework for placement and migration of VMs that takes into account both the network topology as well as network traffic demands, to meet the objective of network power reduction while satisfying as many network demands as possible. We present network power aware VM placement and demand routing as an optimization problem. We show that the problem is NP-complete, and present a fast heuristic for the same. Next, we present the design of a simulator that implements this heuristic and simulates its executions over a data center network with a CLOS topology. Our simulation results using real data center traces demonstrate that, by applying an intelligent VM placement heuristic, VMFlow can achieve 15-20% additional savings in network power while satisfying 5-6 times more network demands as compared to recently proposed techniques for saving network power.
---
paper_title: Network Element Scheduling for Achieving Energy-Aware Data Center Networks

paper_content:

The goal of data center network is to interconnect a massive number of servers so as to provide reliable and scalable computing and storage infrastructure for cloud-based Internet services and data-intensive scientific applications. Recent studies reveal that the network elements consume 10∼20% of the overall power in a data center, which has introduced a challenge to reducing network energy cost without adversely affecting network performance. Considering unique features of traffic patterns and network topologies in data centers, this paper proposes a novel Network Element Scheduling Scheme (NESS) to reduce data center energy consumption from the networking perspective. The core idea is to turn on only a minimal subset of network elements to satisfy routing requirements, and put to sleep or shut down the rest unneeded ones for energy saving. In NESS, the logical network architecture formed by the active elements not only achieves the basic purpose for server interconnections in data centers, but also can support multi-path routing between pairs of hot servers for load balancing. Simulation experiments are performed in representative data center network topologies, and the results demonstrate the effectiveness of NESS in energy conserving on network elements in data centers.
---
paper_title: Energy efficient data center network based on a flexible bandwidth MIMO OFDM optical interconnect

paper_content:

Next generation data centers will have to face an increased amount of network traffic due to emerging applications such as cloud computing. Processing larger data volume leads to higher energy consumption, which in turn causes higher operation expense. Optical interconnects have gained attention recently as a promising solution due to its large bandwidth and high energy efficiency compared to the current networks based on commodity electrical switches. In this paper, we evaluate the energy efficiency of a novel data center network architecture based on optical multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology. By utilizing passive optical switch (cyclic arrayed waveguide grating) and parallel signal detection technology to detect multiple optical channels simultaneously with a single photodetector, this architecture offers high energy efficiency. The comparison with a reference design based on commodity electrical switches shows that the proposed architecture can reduce the power consumption and operation cost significantly while providing higher throughput.
---
paper_title: Power consumption evaluation of hybrid WDM PON networks for data centers

paper_content:

As the requirements for processing power of the datacenters continues to increase rapidly, higher performance networks are required to sustain the increased communication bandwidth demand within the data center. Current data center networks cannot affordably satisfy the required bandwidth of emerging application without consuming excessive power. Optical interconnects provide a viable solution offering high throughput, reduced latency and reduced energy consumption compared to current networks based on commodity switches. This paper presents a novel hybrid approach that use commodity Ethernet switches for intra-rack communication and WDM PON for inter-rack communication. The proposed scheme is based on readily available, passive optical components devices, thus eliminating the power dissipated in Top-of-the-Rack switches for the inter-rack communication. The performance evaluation based on simulation shows up to 10% power reduction with negligible increase on the packet latency.
---
paper_title: On the Complexity of Power Minimization Schemes in Data Center Networks

paper_content:

In this paper, we consider migration of virtual machines in a data center to minimize network power consumption. Network power is consumed when switches are turned on, and conserved when they are turned off; the optimization problem then is to site virtual machines within the data center to achieve connectivity and desired bandwidth while turning on as few switches as possible. Depending upon specifics of the permissible optimization, and topology considerations within the data center, this optimization problem can be easy, or hard. We fully taxonomize the suite of optimization problems in this general space, showing that the most complex problem (placement and routing of virtual machines in a topologically-rich data center network) is NP- hard. We offer a placement technique based on a classic VLSI placement algorithm, and demonstrate efficacy on a trace set derived from a production data center.
---
paper_title: Energy-aware routing in data center network

paper_content:

The goal of data center network is to interconnect the massive number of data center servers, and provide efficient and fault-tolerant routing service to upper-layer applications. To overcome the problem of tree architecture in current practice, many new network architectures are proposed, represented by Fat-Tree, BCube, and etc. A consistent theme in these new architectures is that a large number of network devices are used to achieve 1:1 oversubscription ratio. However, at most time, data center traffic is far below the peak value. The idle network devices will waste significant amount of energy, which is now a headache for many data center owners. In this paper, we discuss how to save energy consumption in high-density data center networks in a routing perspective. We call this kind of routing energy-aware routing. The key idea is to use as few network devices to provide the routing service as possible, with no/little sacrifice on the network performance. Meanwhile, the idle network devices can be shutdown or put into sleep mode for energy saving. We establish the model of energy-aware routing in data center network, and design a heuristic algorithm to achieve the idea. Our simulation in typical data center networks shows that energy-aware routing can effectively save power consumed by network devices.
---
paper_title: ElasticTree: Saving Energy in Data Center Networks

paper_content:

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
---
paper_title: VMPlanner : Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers

paper_content:

In recent years, the power costs of cloud data centers have become a practical concern and have attracted significant attention from both industry and academia. Most of the early works on data center energy efficiency have focused on the biggest power consumers (i.e., computer servers and cooling systems), yet without taking the networking part into consideration. However, recent studies have revealed that the network elements consume 10-20% of the total power in the data center, which poses a great challenge to effectively reducing network power cost without adversely affecting overall network performance. Based on the analysis on topology characteristics and traffic patterns of data centers, this paper presents a novel approach, called VMPlanner, for network power reduction in the virtualization-based data centers. The basic idea of VMPlanner is to optimize both virtual machine placement and traffic flow routing so as to turn off as many unneeded network elements as possible for power saving. We formulate the optimization problem, analyze its hardness, and solve it by designing VMPlanner as a stepwise optimization approach with three approximation algorithms. VMPlanner is implemented and evaluated in a simulated environment with traffic traces collected from a data center test-bed, and the experiment results illustrate the efficacy and efficiency of this approach.
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paper_title: Designing Energy-Efficient Data Center Networks Using Space-Time Optical Interconnection Architectures

paper_content:

This paper considers a space-time interconnection architecture (STIA) based on optical devices and proposes its introduction in data center networks. The power consumption of the STIA is modeled, accounting for the energy proportionality of the optical devices in the STIA. Using such a model, a STIA-based network is designed using three different topologies, tree, folded Clos, and flattened butterfly, and optimized for power efficiency. Results show that, for a fixed topology, small-size STIAs are an energy-efficient solution for data center networks and allow a power reduction of more than an order of magnitude with respect to the Ethernet-based network. The comparison for the same bisection bandwidth shows that folded Clos and flattened butterfly outperform tree, whose power consumption is strongly dependent on the oversubscription ratio selected.
---
paper_title: How can architecture help to reduce energy consumption in data center networking

paper_content:

Reducing the power consumption of data centers has recently been received much attention from the research community and the industry alike. It is because the benefits are manifold: for the data centers themselves and towards the environment. A number of issues concerning with the consumption of the servers or the switches have been investigated. However, the energy requirement of the data center architecture has not yet been sufficiently addressed. In this paper, we address this issue and make two key contributions. Before delving into the details of possible solutions for reducing power of existing data center architectures, we first characterize the impact of architectural parameters on the power consumption of data centers by presenting preliminary results on the power consumption of state-of-the-art data center structures, namely BCube [8], DCell [9], and Fat-tree [1, 11, 7]. Secondly, based on the insights and lessons learnt from the analysis, we present our vision on possible practical solutions to reduce the energy usage of data center networking.
---
paper_title: Energy-aware data centre management

paper_content:

Cloud computing is one way in which communications within and between data centres can be optimised by using resources which are physically close to the client, are exposed to lower electricity costs, contribute a smaller carbon footprint or have residual resources sufficient to fulfil Quality of Service requirements. Optimisation of activity involving data centres is a next generation network management objective due to continued growth in the number of plants and volume of operations within, factors which contribute to environmental concerns associated with energy consumption and carbon emissions from data centre facilities when renewable energy resources are not used. In this paper, we present an algorithmic mechanism developed to automate selection of a data centre in response to application requests, the Data Centre (DC) Energy-Efficient Context-Aware Broker (e-CAB). Through integration of the DCe-CAB in a case study scenario, operational improvement through reduction of carbon emission and balancing of other performance-related attributes including delay and financial cost is achieved, validating the DCe-CAB's positive impact.
---
paper_title: A distributed energy saving approach for Ethernet switches in data centers

paper_content:

With popularity of data centers, energy efficiency of Ethernet switches in them is becoming a critical issue. Most existing energy saving approaches use a centralized methodology that assumes global knowledge of data center networks. Though these approaches can achieve nearly optimal energy saving for static traffic patterns, they are not suitable when the traffic patterns can change rapidly or the data centers have a large size. To overcome these limitations, this paper proposes a novel distributed approach called eAware that dynamically idles a port or a switch to save energy by examining the queue lengths and utilizations at switch ports. Through extensive simulations in ns-2, we compare eAware with an existing energy oblivious approach, showing that eAware can save 30%–50% on the total energy consumption by switches in data centers, and only increases the average end-to-end delay of packets by 3%–20% and the packet loss ratio by 0%–0.9%.
---
paper_title: Application of the Snowflake Structure in the Network Structure of Electric Power Enterprise Data Center

paper_content:

The network structure of electric power enterprise data center is one of today's data center researches, which aims at creating a better, safer and more efficient network structure. The main content of this article involves the application of a new-type network structure of data center--snowflake structure in electric power enterprises. First of all, it introduces the network structures of today's data centers and the snowflake network structure. Then it illustrates three characteristics of snowflake structure in terms of transmission bandwidth, throughput bottlenecks and network delay, and compares snowflake structure with Dcell and Bcube in order to highlight the superiority of snowflake structure. Finally, according to the characteristics of snowflake structure, it describes the research on the application of snowflake structure in the electric power enterprise data center.
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paper_title: A Comparison Study of Energy Proportionality of Data Center Network Architectures

paper_content:

Today's data center networks consume a great amount of energy, which significantly aggravates the operational cost of data centers and the carbon footprint. It is an ideal objective for operators to make the power consumption of data center networks proportional to the amount of network loads they carry. To this end, many recent researches are focusing on two representative methods: device-level sleeping technology and network-wide energy aware routing. It is important for operators to understand what effects these energy conservation methods have on improving the network energy proportionality. In the paper, we make a comparison study on the energy proportionality of data center networks, based on regular routing and energy-aware routing. Specifically, we first choose several typical data center network architectures and equalize their network performance. Afterwards, we analyze the maximum power consumption of data center networks without using any energy conservation strategy, and compare their energy proportionality when employing the sleeping technology and energy-aware routing respectively.
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paper_title: PCube: Improving Power Efficiency in Data Center Networks

paper_content:

To alleviate the growing concern of energy waste in networked devices, we present PCube, a server-centric data center structure that conserves energy by varying bandwidth availability based on traffic demand. PCube not only supports a low-power mode for existing data centers offering full bisection bandwidth without hardware modification or re-wiring, but also provides an alternative for new data centers at a lower construction cost. The bandwidth demand could be dynamic and scalable in the optimal way when considering conserving the energy waste. To further reduce the cost, we take advantage of traffic locality, and propose Hybrid PCube, in order to offer different bandwidth to different servers. We use samples of traffic from a real-world production data center with full bisection bandwidth across thousands of servers, and evaluate our proposed algorithm using these collected samples. Our experimental results have shown convincing evidence that the proposed algorithm is able to substantially reduce energy costs incurred by networked devices in data centers.
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paper_title: Maximum Flow Minimum Energy routing for ExaScale Cloud Computing systems

paper_content:

This paper explores the feasibility of Exascale Cloud Computing over the Nobel-EU (European Union) IP backbone network. The EU represents an attractive environment for Exascale Cloud Computing, due to its well-established IP infrastructure with relatively low edge distances. An Exascale Cloud Computing system linking hundreds of data-centers can interconnect potentially millions of servers, considerably larger than the world's most powerful supercomputer. However, the US Dept. of Energy has recently concluded that cloud computing is too expensive and suitable only for scientific applications with minimal communications requirements. This paper explores a Future-Internet network to address these concerns. The network combines several technologies; (i) a QoS-aware router scheduling algorithm, (ii) a flow resource-reservation signalling algorithm, and (iii) flow aggregation, to establish highly-efficient guaranteed-rate connections between data-centers. A Maximum-Flow Minimum-Energy routing algorithm is used to route high-capacity ”trunks” between data-centers with minimum energy requirements. The traffic flows between data-centers are aggregated onto the trunks, to achieve exceptionally low latencies with improved link utilizations and energy-efficiencies. The high packet loss rates and large queueing delays of traditional Best-Effort Internet are eliminated, and the latency over the cloud is reduced to the fiber latency. The average fiber latencies over the Nobel-EU network are a few milliseconds, and they can be mitigated with multithreading. The bisection bandwidth of the cloud can be improved to match the demand by activating dark fiber. By lowering latencies, the utilization of the Internet data-centers will also increase, further improving overall energy efficiency. The proposed Future Internet network can improve the utilization and energy efficiency of both the communications and computations in Cloud Computing systems.
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paper_title: Energy-Saving Virtual Machine Placement in Cloud Data Centers

paper_content:

In cloud data centers, different mapping relationships between virtual machines (VMs) and physical machines (PMs) cause different resource utilization, therefore, how to place VMs on PMs to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. The existing VM placement schemes are to optimize physical server resources utilization or network resources utilization, but few of them focuses on optimizing multiple resources utilization simultaneously. To address the issue, this paper proposes a VM placement scheme meeting multiple resource constraints, such as the physical server size (CPU, memory, storage, bandwidth, etc.) and network link capacity to improve resource utilization and reduce both the number of active physical servers and network elements so as to finally reduce energy consumption. Since VM placement problem is abstracted as a combination of bin packing problem and quadratic assignment problem, which is also known as a classic combinatorial optimization and NP-hard problem, we design a novel greedy algorithm by combining minimum cut with the best-fit, and the simulations show that our solution achieves better results.
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paper_title: Honeyguide: A VM migration-aware network topology for saving energy consumption in data center networks

paper_content:

Network elements consume 10–20% of the total power in data centers. Today's network elements are not energy-proportional and consume constant energy1 regardless of the traffic amounts. Thus, turning off unused network switches is the most efficient way of saving energy consumption of data center networks. This paper presents Honeyguide, an energy optimizer for data center networks that not only turns off inactive switches but also increases the number of inactive switches for energy-efficiency. To this end, Honeyguide combines two techniques: 1) virtual machine (VM) and traffic consolidation, and 2) a slight extension to existing tree-based topologies. Honeyguide has the following advantages. VM consolidation, which is gracefully combined with traffic consolidation, can handle severe requirements on fault tolerance. It can be introduced into existing data centers without replacing already-deployed tree-based topologies. Our simulation results demonstrate that Honeyguide can save more energy consumption of network elements than conventional VM migration schemes, and the savings are up to 7.8% in a fat tree with k = 12.
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paper_title: Calculating the Minimum Bounds of Energy Consumption for Cloud Networks

paper_content:

This paper is aiming at facilitating the energy-efficient operation of an integrated optical network and IT infrastructure. In this context we propose an energy-efficient routing algorithm for provisioning of IT services that originate from specific source sites and which need to be executed by suitable IT resources (e.g. data centers). The routing approach followed is anycast, since the requirement for the IT services is the delivery of results, while the exact location of the execution of the job can be freely chosen. In this scenario, energy efficiency is achieved by identifying the least energy consuming IT and network resources required to support the services, enabling the switching off of any unused network and IT resources. Our results show significant energy savings that can reach up to 55% compared to energy-unaware schemes, depending on the granularity with which a data center is able to switch on/off servers.
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paper_title: Energy-Saving Virtual Machine Placement in Cloud Data Centers

paper_content:

In cloud data centers, different mapping relationships between virtual machines (VMs) and physical machines (PMs) cause different resource utilization, therefore, how to place VMs on PMs to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. The existing VM placement schemes are to optimize physical server resources utilization or network resources utilization, but few of them focuses on optimizing multiple resources utilization simultaneously. To address the issue, this paper proposes a VM placement scheme meeting multiple resource constraints, such as the physical server size (CPU, memory, storage, bandwidth, etc.) and network link capacity to improve resource utilization and reduce both the number of active physical servers and network elements so as to finally reduce energy consumption. Since VM placement problem is abstracted as a combination of bin packing problem and quadratic assignment problem, which is also known as a classic combinatorial optimization and NP-hard problem, we design a novel greedy algorithm by combining minimum cut with the best-fit, and the simulations show that our solution achieves better results.
---
paper_title: Energy efficient data center network based on a flexible bandwidth MIMO OFDM optical interconnect

paper_content:

Next generation data centers will have to face an increased amount of network traffic due to emerging applications such as cloud computing. Processing larger data volume leads to higher energy consumption, which in turn causes higher operation expense. Optical interconnects have gained attention recently as a promising solution due to its large bandwidth and high energy efficiency compared to the current networks based on commodity electrical switches. In this paper, we evaluate the energy efficiency of a novel data center network architecture based on optical multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology. By utilizing passive optical switch (cyclic arrayed waveguide grating) and parallel signal detection technology to detect multiple optical channels simultaneously with a single photodetector, this architecture offers high energy efficiency. The comparison with a reference design based on commodity electrical switches shows that the proposed architecture can reduce the power consumption and operation cost significantly while providing higher throughput.
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paper_title: VMFlow: Leveraging VM Mobility to Reduce Network Power Costs in Data Centers

paper_content:

Networking costs play an important role in the overall costs of a modern data center. Network power, for example, has been estimated at 10-20% of the overall data center power consumption. Traditional power saving techniques in data centers focus on server power reduction through Virtual Machine (VM) migration and server consolidation, without taking into account the network topology and the current network traffic. On the other hand, recent techniques to save network power have not yet utilized the various degrees of freedom that current and future data centers will soon provide. These include VM migration capabilities across the entire data center network, on demand routing through programmable control planes, and high bisection bandwidth networks. ::: ::: This paper presents VMFlow: a framework for placement and migration of VMs that takes into account both the network topology as well as network traffic demands, to meet the objective of network power reduction while satisfying as many network demands as possible. We present network power aware VM placement and demand routing as an optimization problem. We show that the problem is NP-complete, and present a fast heuristic for the same. Next, we present the design of a simulator that implements this heuristic and simulates its executions over a data center network with a CLOS topology. Our simulation results using real data center traces demonstrate that, by applying an intelligent VM placement heuristic, VMFlow can achieve 15-20% additional savings in network power while satisfying 5-6 times more network demands as compared to recently proposed techniques for saving network power.
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paper_title: Network Element Scheduling for Achieving Energy-Aware Data Center Networks

paper_content:

The goal of data center network is to interconnect a massive number of servers so as to provide reliable and scalable computing and storage infrastructure for cloud-based Internet services and data-intensive scientific applications. Recent studies reveal that the network elements consume 10∼20% of the overall power in a data center, which has introduced a challenge to reducing network energy cost without adversely affecting network performance. Considering unique features of traffic patterns and network topologies in data centers, this paper proposes a novel Network Element Scheduling Scheme (NESS) to reduce data center energy consumption from the networking perspective. The core idea is to turn on only a minimal subset of network elements to satisfy routing requirements, and put to sleep or shut down the rest unneeded ones for energy saving. In NESS, the logical network architecture formed by the active elements not only achieves the basic purpose for server interconnections in data centers, but also can support multi-path routing between pairs of hot servers for load balancing. Simulation experiments are performed in representative data center network topologies, and the results demonstrate the effectiveness of NESS in energy conserving on network elements in data centers.
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paper_title: Energy-efficient, high-performance optoelectronic packet switching for intra-data center network

paper_content:

An energy-efficient, high-performance optoelectronic packet switching for intra-data center (DC) network is presented, in which hybrid optoelectronic packet routers (HOERs) are interconnected with 100 Gbps (25 Gbps×4 wavelengths) links. A novel “Express path (ExP)” is introduced to enable the flow control. Packets, which are a part of a flow, can be bypassed the intermediate nodes and directly forwarded to the destination through the ExP. This bypass allows substantial offload packets from the HOERs, while, on the other hand, an individual packet is processed and forwarded by the HOERs. OpenFlow controls both the flows and virtual machines (VMs) of server cluster in a centralized fashion. As a consequence, drastic reduction of the power consumption as well as low latency will be demonstrated with all-out proposed efforts in the hardware and the smart networking.
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paper_title: Power consumption evaluation of hybrid WDM PON networks for data centers

paper_content:

As the requirements for processing power of the datacenters continues to increase rapidly, higher performance networks are required to sustain the increased communication bandwidth demand within the data center. Current data center networks cannot affordably satisfy the required bandwidth of emerging application without consuming excessive power. Optical interconnects provide a viable solution offering high throughput, reduced latency and reduced energy consumption compared to current networks based on commodity switches. This paper presents a novel hybrid approach that use commodity Ethernet switches for intra-rack communication and WDM PON for inter-rack communication. The proposed scheme is based on readily available, passive optical components devices, thus eliminating the power dissipated in Top-of-the-Rack switches for the inter-rack communication. The performance evaluation based on simulation shows up to 10% power reduction with negligible increase on the packet latency.
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paper_title: On the Complexity of Power Minimization Schemes in Data Center Networks

paper_content:

In this paper, we consider migration of virtual machines in a data center to minimize network power consumption. Network power is consumed when switches are turned on, and conserved when they are turned off; the optimization problem then is to site virtual machines within the data center to achieve connectivity and desired bandwidth while turning on as few switches as possible. Depending upon specifics of the permissible optimization, and topology considerations within the data center, this optimization problem can be easy, or hard. We fully taxonomize the suite of optimization problems in this general space, showing that the most complex problem (placement and routing of virtual machines in a topologically-rich data center network) is NP- hard. We offer a placement technique based on a classic VLSI placement algorithm, and demonstrate efficacy on a trace set derived from a production data center.
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paper_title: Energy-aware routing in data center network

paper_content:

The goal of data center network is to interconnect the massive number of data center servers, and provide efficient and fault-tolerant routing service to upper-layer applications. To overcome the problem of tree architecture in current practice, many new network architectures are proposed, represented by Fat-Tree, BCube, and etc. A consistent theme in these new architectures is that a large number of network devices are used to achieve 1:1 oversubscription ratio. However, at most time, data center traffic is far below the peak value. The idle network devices will waste significant amount of energy, which is now a headache for many data center owners. In this paper, we discuss how to save energy consumption in high-density data center networks in a routing perspective. We call this kind of routing energy-aware routing. The key idea is to use as few network devices to provide the routing service as possible, with no/little sacrifice on the network performance. Meanwhile, the idle network devices can be shutdown or put into sleep mode for energy saving. We establish the model of energy-aware routing in data center network, and design a heuristic algorithm to achieve the idea. Our simulation in typical data center networks shows that energy-aware routing can effectively save power consumed by network devices.
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paper_title: GreenVLAN: An energy-efficient approach for VLAN design

paper_content:

The greening of the Internet has become an important research issue due to the huge energy consumption of the Internet. In this paper, we explore network-level power saving mechanisms in the context of virtual local area networks (VLANs) given their importance and prevalence in enterprise, campus and Data Center Networks (DCNs). After investigating the disadvantages of current VLAN design method, we propose the GreenVLAN approach, which aims at reducing the power usage in the next generation Energy-Efficient Ethernet. The proposed GreenVLAN approach is formulated as a nonlinear integer programming problem with the total energy consumption as the objective to be minimized. Besides, we develop a practical heuristic algorithm to solve the proposed model and the complexity of the algorithm is analyzed. Our experiments on both simulated topology and real-world campus network demonstrate that Green-VLAN could achieve considerable power saving (reduce the power consumption of Ethernet links by about 27%∼53% for a typical VLAN configuration) compared with current VLAN practice.
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paper_title: Energy Aware Networked Cloud Mapping

paper_content:

Cloud computing has emerged as the computing paradigm that enables the delivery of utility-based IT services to users. The hyper-growth of Cloud computing has led to increased power consumption with significant consequences both in terms of environmental and operational costs. Hence, over the last years, attention has been drawn to optimizing energy consumption at the data center, aimed at the reduction of carbon footprints. However the world of Cloud Computing is constantly developing, with new concepts introduced while additional challenges arise. In this paper, a method for energy efficient resource allocation is proposed, in the context of a networked cloud environment. The method employs dynamic server consolidation by periodic VM migration. The approach is validated conducting performance evaluation via simulation, while it is compared against energy aware / non energy aware methods, using a set of both power indication and resource allocation metrics.
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paper_title: Energy models driven green routing for data centers

paper_content:

Energy consumption is becoming a serious issue for data centers. Minimizing the energy consumption of a data center is a complex problem. It consists of developing energy models for servers and network elements and investigating energy-aware (green) routing strategies using these models. In this paper, we adapt energy models for servers and network elements in a data center. The server energy model incorporates the impact of temperature and voltage of a server on its leakage energy. Using the server and network energy models, we propose a green routing scheme that minimizes the total combined energy consumption of servers and network elements in a data center under dynamic traffic. The proposed green routing scheme uses dynamic voltage scaling, rate adaptation, and anycast transmission for minimizing the total energy consumption. Extensive simulation results validate the effectiveness of the proposed green routing in minimizing the total energy consumption of a data center as compared to well-known existing approaches.
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paper_title: An Energy Aware Network Management Approach Using Server Profiling in 'Green' Clouds

paper_content:

Clouds and data centres are significant consumers of power. There are however, opportunities for optimising carbon cost here as resource redundancy is provisioned extensively. Data centre resources, and subsequently clouds which support them, are traditionally organised into tiers; switch-off activity when managing redundant resources therefore occurs in an approach which exploits cost advantages associated with closing down entire network portions. We suggest however, an alternative approach to optimise cloud operation while maintaining application QoS: Simulation experiments identify that network operation can be optimised by selecting servers which process traffic at a rate that more closely matches the packet arrival rate, and resources which provision excessive capacity additional to that required may be powered off for improved efficiency. This recognises that there is a point in server speed at which performance is optimised, and operation which is greater than or less than this rate will not achieve optimisation. A series of policies have been defined in this work for integration into cloud management procedures; performance results from their implementation and evaluation in simulation show improved efficiency by selecting servers based on these relationships.
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paper_title: Energy Aware Network Operations

paper_content:

Networking devices today consume a non-trivial amount of energy and it has been shown that this energy consumption is largely independent of the load through the devices. With a strong need to curtail the rising operational costs of IT infrastructure, there is a tremendous opportunity for introducing energy awareness in the design and operation of enterprise and data center networks. We focus on these networks as they are under the control of a single administrative domain in which network-wide control can be consistently applied. In this paper, we describe and analyze three approaches to saving energy in single administrative domain networks, without significantly impacting the networks' ability to provide the expected levels of performance and availability. We also explore the trade-offs between conserving energy and meeting performance and availability requirements. We conduct an extensive case study of our algorithms by simulating a real Web 2.0 workload in a real data center network topology using power characterizations that we obtain from real network hardware. Our results indicate that for our workload and data center scenario, 16% power savings (with no performance penalty and small decrease in availability) can be obtained merely by appropriately adjusting the active network elements (links). Significant additional savings (up to 75%) can be obtained by incorporating network traffic management and server workload consolidation.
---
paper_title: VMPlanner : Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers

paper_content:

In recent years, the power costs of cloud data centers have become a practical concern and have attracted significant attention from both industry and academia. Most of the early works on data center energy efficiency have focused on the biggest power consumers (i.e., computer servers and cooling systems), yet without taking the networking part into consideration. However, recent studies have revealed that the network elements consume 10-20% of the total power in the data center, which poses a great challenge to effectively reducing network power cost without adversely affecting overall network performance. Based on the analysis on topology characteristics and traffic patterns of data centers, this paper presents a novel approach, called VMPlanner, for network power reduction in the virtualization-based data centers. The basic idea of VMPlanner is to optimize both virtual machine placement and traffic flow routing so as to turn off as many unneeded network elements as possible for power saving. We formulate the optimization problem, analyze its hardness, and solve it by designing VMPlanner as a stepwise optimization approach with three approximation algorithms. VMPlanner is implemented and evaluated in a simulated environment with traffic traces collected from a data center test-bed, and the experiment results illustrate the efficacy and efficiency of this approach.
---
paper_title: How can architecture help to reduce energy consumption in data center networking

paper_content:

Reducing the power consumption of data centers has recently been received much attention from the research community and the industry alike. It is because the benefits are manifold: for the data centers themselves and towards the environment. A number of issues concerning with the consumption of the servers or the switches have been investigated. However, the energy requirement of the data center architecture has not yet been sufficiently addressed. In this paper, we address this issue and make two key contributions. Before delving into the details of possible solutions for reducing power of existing data center architectures, we first characterize the impact of architectural parameters on the power consumption of data centers by presenting preliminary results on the power consumption of state-of-the-art data center structures, namely BCube [8], DCell [9], and Fat-tree [1, 11, 7]. Secondly, based on the insights and lessons learnt from the analysis, we present our vision on possible practical solutions to reduce the energy usage of data center networking.
---
paper_title: Energy-aware data centre management

paper_content:

Cloud computing is one way in which communications within and between data centres can be optimised by using resources which are physically close to the client, are exposed to lower electricity costs, contribute a smaller carbon footprint or have residual resources sufficient to fulfil Quality of Service requirements. Optimisation of activity involving data centres is a next generation network management objective due to continued growth in the number of plants and volume of operations within, factors which contribute to environmental concerns associated with energy consumption and carbon emissions from data centre facilities when renewable energy resources are not used. In this paper, we present an algorithmic mechanism developed to automate selection of a data centre in response to application requests, the Data Centre (DC) Energy-Efficient Context-Aware Broker (e-CAB). Through integration of the DCe-CAB in a case study scenario, operational improvement through reduction of carbon emission and balancing of other performance-related attributes including delay and financial cost is achieved, validating the DCe-CAB's positive impact.
---
paper_title: Energy-saving self-configuring networked data centers

paper_content:

In this paper, we develop the optimal minimum-energy scheduler for the dynamic online joint allocation of the task sizes, computing rates, communication rates and communication powers in virtualized Networked Data Centers (NetDCs) that operates under hard per-job delay-constraints. The referred NetDC's infrastructure is composed by multiple frequency-scalable Virtual Machines (VMs), that are interconnected by a bandwidth and power-limited switched Local Area Network (LAN). Due to the nonlinear power-vs.-communication rate relationship, the resulting Computing-Communication Optimization Problem (CCOP) is inherently nonconvex. In order to analytically compute the exact solution of the CCOP, we develop a solving approach that relies on the following two main steps: (i) we prove that the CCOP retains a loosely coupled structure, that allows us to perform the lossless decomposition of the CCOP into the cascade of two simpler sub-problems; and, (ii) we prove that the coupling between the aforementioned sub-problems is provided by a (scalar) constraint, that is linear in the offered workload. The resulting optimal scheduler is amenable of scalable and distributed online implementation and its analytical characterization is in closed-form. After numerically testing its actual performance under randomly time-varying synthetically generated and real-world measured workload traces, we compare the obtained performance with the corresponding ones of some state-of-the-art static and sequential schedulers.
---
paper_title: A distributed energy saving approach for Ethernet switches in data centers

paper_content:

With popularity of data centers, energy efficiency of Ethernet switches in them is becoming a critical issue. Most existing energy saving approaches use a centralized methodology that assumes global knowledge of data center networks. Though these approaches can achieve nearly optimal energy saving for static traffic patterns, they are not suitable when the traffic patterns can change rapidly or the data centers have a large size. To overcome these limitations, this paper proposes a novel distributed approach called eAware that dynamically idles a port or a switch to save energy by examining the queue lengths and utilizations at switch ports. Through extensive simulations in ns-2, we compare eAware with an existing energy oblivious approach, showing that eAware can save 30%–50% on the total energy consumption by switches in data centers, and only increases the average end-to-end delay of packets by 3%–20% and the packet loss ratio by 0%–0.9%.
---
paper_title: Benefits of green energy and proportionality in high speed wide area networks connecting data centers

paper_content:

Many companies deploy multiple data centers across the globe to satisfy the dramatically increased computational demand. Wide area connectivity between such geographically distributed data centers has an important role to ensure both the quality of service, and, as bandwidths increase to 100Gbps and beyond, as an efficient way to dynamically distribute the computation. The energy cost of data transmission is dominated by the router power consumption, which is unfortunately not energy proportional. In this paper we not only quantify the performance benefits of leveraging the network to run more jobs, but also analyze its energy impact. We compare the benefits of redesigning routers to be more energy efficient to those obtained by leveraging locally available green energy as a complement to the brown energy supply. Furthermore, we design novel green energy aware routing policies for wide area traffic and compare to state-of-the-art shortest path routing algorithm. Our results indicate that using energy proportional routers powered in part by green energy along with our new routing algorithm results in 10x improvement in per router energy efficiency with 36% average increase in the number of jobs completed.
---
paper_title: A Comparison Study of Energy Proportionality of Data Center Network Architectures

paper_content:

Today's data center networks consume a great amount of energy, which significantly aggravates the operational cost of data centers and the carbon footprint. It is an ideal objective for operators to make the power consumption of data center networks proportional to the amount of network loads they carry. To this end, many recent researches are focusing on two representative methods: device-level sleeping technology and network-wide energy aware routing. It is important for operators to understand what effects these energy conservation methods have on improving the network energy proportionality. In the paper, we make a comparison study on the energy proportionality of data center networks, based on regular routing and energy-aware routing. Specifically, we first choose several typical data center network architectures and equalize their network performance. Afterwards, we analyze the maximum power consumption of data center networks without using any energy conservation strategy, and compare their energy proportionality when employing the sleeping technology and energy-aware routing respectively.
---
paper_title: PCube: Improving Power Efficiency in Data Center Networks

paper_content:

To alleviate the growing concern of energy waste in networked devices, we present PCube, a server-centric data center structure that conserves energy by varying bandwidth availability based on traffic demand. PCube not only supports a low-power mode for existing data centers offering full bisection bandwidth without hardware modification or re-wiring, but also provides an alternative for new data centers at a lower construction cost. The bandwidth demand could be dynamic and scalable in the optimal way when considering conserving the energy waste. To further reduce the cost, we take advantage of traffic locality, and propose Hybrid PCube, in order to offer different bandwidth to different servers. We use samples of traffic from a real-world production data center with full bisection bandwidth across thousands of servers, and evaluate our proposed algorithm using these collected samples. Our experimental results have shown convincing evidence that the proposed algorithm is able to substantially reduce energy costs incurred by networked devices in data centers.
---
paper_title: A virtual network to achieve low energy consumption in optical large-scale datacenter

paper_content:

A data center network should provide communication with sufficiently large bandwidth and small delay between all servers. On the other hand, energy consumption of the data center network should be minimized. To satisfy all of the above requirements, in this paper, we introduce the virtual network configured over the data center network constructed of the optical cross connects (OXCs) and the electronic switches. We design the virtual network topology (VNT) so as to achieve sufficiently large bandwidth and small delay with small energy consumption. To calculate the suitable VNT in a short period, we propose the topology called Generalized Flattened Butterfly and a method to set the parameters so as to suit the current condition. In our evaluation, we clarify that our method achieves the sufficient bandwidth and the target maximum number of hops between top-of rack(ToR) switches with small energy consumption.
---
paper_title: Maximum Flow Minimum Energy routing for ExaScale Cloud Computing systems

paper_content:

This paper explores the feasibility of Exascale Cloud Computing over the Nobel-EU (European Union) IP backbone network. The EU represents an attractive environment for Exascale Cloud Computing, due to its well-established IP infrastructure with relatively low edge distances. An Exascale Cloud Computing system linking hundreds of data-centers can interconnect potentially millions of servers, considerably larger than the world's most powerful supercomputer. However, the US Dept. of Energy has recently concluded that cloud computing is too expensive and suitable only for scientific applications with minimal communications requirements. This paper explores a Future-Internet network to address these concerns. The network combines several technologies; (i) a QoS-aware router scheduling algorithm, (ii) a flow resource-reservation signalling algorithm, and (iii) flow aggregation, to establish highly-efficient guaranteed-rate connections between data-centers. A Maximum-Flow Minimum-Energy routing algorithm is used to route high-capacity ”trunks” between data-centers with minimum energy requirements. The traffic flows between data-centers are aggregated onto the trunks, to achieve exceptionally low latencies with improved link utilizations and energy-efficiencies. The high packet loss rates and large queueing delays of traditional Best-Effort Internet are eliminated, and the latency over the cloud is reduced to the fiber latency. The average fiber latencies over the Nobel-EU network are a few milliseconds, and they can be mitigated with multithreading. The bisection bandwidth of the cloud can be improved to match the demand by activating dark fiber. By lowering latencies, the utilization of the Internet data-centers will also increase, further improving overall energy efficiency. The proposed Future Internet network can improve the utilization and energy efficiency of both the communications and computations in Cloud Computing systems.
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paper_title: Energy-Saving Virtual Machine Placement in Cloud Data Centers

paper_content:

In cloud data centers, different mapping relationships between virtual machines (VMs) and physical machines (PMs) cause different resource utilization, therefore, how to place VMs on PMs to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. The existing VM placement schemes are to optimize physical server resources utilization or network resources utilization, but few of them focuses on optimizing multiple resources utilization simultaneously. To address the issue, this paper proposes a VM placement scheme meeting multiple resource constraints, such as the physical server size (CPU, memory, storage, bandwidth, etc.) and network link capacity to improve resource utilization and reduce both the number of active physical servers and network elements so as to finally reduce energy consumption. Since VM placement problem is abstracted as a combination of bin packing problem and quadratic assignment problem, which is also known as a classic combinatorial optimization and NP-hard problem, we design a novel greedy algorithm by combining minimum cut with the best-fit, and the simulations show that our solution achieves better results.
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paper_title: Honeyguide: A VM migration-aware network topology for saving energy consumption in data center networks

paper_content:

Network elements consume 10–20% of the total power in data centers. Today's network elements are not energy-proportional and consume constant energy1 regardless of the traffic amounts. Thus, turning off unused network switches is the most efficient way of saving energy consumption of data center networks. This paper presents Honeyguide, an energy optimizer for data center networks that not only turns off inactive switches but also increases the number of inactive switches for energy-efficiency. To this end, Honeyguide combines two techniques: 1) virtual machine (VM) and traffic consolidation, and 2) a slight extension to existing tree-based topologies. Honeyguide has the following advantages. VM consolidation, which is gracefully combined with traffic consolidation, can handle severe requirements on fault tolerance. It can be introduced into existing data centers without replacing already-deployed tree-based topologies. Our simulation results demonstrate that Honeyguide can save more energy consumption of network elements than conventional VM migration schemes, and the savings are up to 7.8% in a fat tree with k = 12.
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paper_title: ElasticTree: Saving Energy in Data Center Networks

paper_content:

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
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paper_title: Calculating the Minimum Bounds of Energy Consumption for Cloud Networks

paper_content:

This paper is aiming at facilitating the energy-efficient operation of an integrated optical network and IT infrastructure. In this context we propose an energy-efficient routing algorithm for provisioning of IT services that originate from specific source sites and which need to be executed by suitable IT resources (e.g. data centers). The routing approach followed is anycast, since the requirement for the IT services is the delivery of results, while the exact location of the execution of the job can be freely chosen. In this scenario, energy efficiency is achieved by identifying the least energy consuming IT and network resources required to support the services, enabling the switching off of any unused network and IT resources. Our results show significant energy savings that can reach up to 55% compared to energy-unaware schemes, depending on the granularity with which a data center is able to switch on/off servers.
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paper_title: Designing Energy-Efficient Data Center Networks Using Space-Time Optical Interconnection Architectures

paper_content:

This paper considers a space-time interconnection architecture (STIA) based on optical devices and proposes its introduction in data center networks. The power consumption of the STIA is modeled, accounting for the energy proportionality of the optical devices in the STIA. Using such a model, a STIA-based network is designed using three different topologies, tree, folded Clos, and flattened butterfly, and optimized for power efficiency. Results show that, for a fixed topology, small-size STIAs are an energy-efficient solution for data center networks and allow a power reduction of more than an order of magnitude with respect to the Ethernet-based network. The comparison for the same bisection bandwidth shows that folded Clos and flattened butterfly outperform tree, whose power consumption is strongly dependent on the oversubscription ratio selected.
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paper_title: Power consumption evaluation of all-optical data center networks

paper_content:

Cloud computing and web emerging applications have created the need for more powerful data centers. These data centers need high bandwidth interconnects that can sustain the high interaction between the web-, application- and database-servers. Data center networks based on electronic packet switches will have to consume excessive power in order to satisfy the required communication bandwidth of future data centers. Optical interconnects have gained attention recently as a promising energy efficient solution offering high throughput, low latency and reduced energy consumption compared to current networks based on commodity switches. This paper presents a comparison on the power consumption of several optical interconnection schemes based on AWGRs, Wavelength Selective Switches (WSS) or Semiconductor Optical Amplifiers (SOAs). Based on a thorough analysis of each architecture, it is shown that optical interconnects can achieve at least an order of magnitude higher energy efficiency compared to current data center networks based on electrical packet based switches and they could contribute to greener IT network infrastructures.
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paper_title: Reducing Total Power Consumption Method in Cloud Computing Environments

paper_content:

The widespread use of cloud computing services is expected to increase the power consumed by ICT equipment in cloud computing environments rapidly. This paper first identifies the need of the collaboration among servers, the communication network and the power network, in order to reduce the total power consumption by the entire ICT equipment in cloud computing environments. Five fundamental policies for the collaboration are proposed and the algorithm to realize each collaboration policy is outlined. Next, this paper proposes possible signaling sequences to exchange information on power consumption between network and servers, in order to realize the proposed collaboration policy. Then, in order to reduce the power consumption by the network, this paper proposes a method of estimating the volume of power consumption by all network devices simply and assigning it to an individual user.
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paper_title: Enhancing data centre networking using energy aware optical interconnects

paper_content:

In a fast changing world where information technology drives economic prosperity, the number of data centres has grown significantly in the past few years. These data centres require large amount of energy in order to meet up with increasing demands. An overview of energy efficient optical interconnects as a means of reducing energy consumption without compromising speed and accuracy was presented. New methods by which energy efficiency can be achieved using OCDMA multiplexing techniques for future optical interconnections were discussed. We also presented some challenges that might inhibit effective implementation of the OCDMA multiplexing scheme.
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paper_title: Energy efficient data center network based on a flexible bandwidth MIMO OFDM optical interconnect

paper_content:

Next generation data centers will have to face an increased amount of network traffic due to emerging applications such as cloud computing. Processing larger data volume leads to higher energy consumption, which in turn causes higher operation expense. Optical interconnects have gained attention recently as a promising solution due to its large bandwidth and high energy efficiency compared to the current networks based on commodity electrical switches. In this paper, we evaluate the energy efficiency of a novel data center network architecture based on optical multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology. By utilizing passive optical switch (cyclic arrayed waveguide grating) and parallel signal detection technology to detect multiple optical channels simultaneously with a single photodetector, this architecture offers high energy efficiency. The comparison with a reference design based on commodity electrical switches shows that the proposed architecture can reduce the power consumption and operation cost significantly while providing higher throughput.
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paper_title: ElasticTree: Saving Energy in Data Center Networks

paper_content:

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
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paper_title: Design of energy-efficient cloud systems via network and resource virtualization

paper_content:

Data centers play a crucial role in the delivery of cloud services by enabling on-demand access to the shared resources such as software, platform and infrastructure. Virtual machine VM allocation is one of the challenging tasks in data center management since user requirements, typically expressed as service-level agreements, have to be met with the minimum operational expenditure. Despite their huge processing and storage facilities, data centers are among the major contributors to greenhouse gas emissions of IT services. In this paper, we propose a holistic approach for a large-scale cloud system where the cloud services are provisioned by several data centers interconnected over the backbone network. Leveraging the possibility to virtualize the backbone topology in order to bypass IP routers, which are major power consumers in the core network, we propose a mixed integer linear programming MILP formulation for VM placement that aims at minimizing both power consumption at the virtualized backbone network and resource usage inside data centers. Since the general holistic MILP formulation requires heavy and long-running computations, we partition the problem into two sub-problems, namely, intra and inter-data center VM placement. In addition, for the inter-data center VM placement, we also propose a heuristic to solve the virtualized backbone topology reconfiguration computation in reasonable time. We thoroughly assessed the performance of our proposed solution, comparing it with another notable MILP proposal in the literature; collected experimental results show the benefit of the proposed management scheme in terms of power consumption, resource utilization and fairness for medium size data centers. Copyright © 2013 John Wiley & Sons, Ltd.
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paper_title: A distributed energy saving approach for Ethernet switches in data centers

paper_content:

With popularity of data centers, energy efficiency of Ethernet switches in them is becoming a critical issue. Most existing energy saving approaches use a centralized methodology that assumes global knowledge of data center networks. Though these approaches can achieve nearly optimal energy saving for static traffic patterns, they are not suitable when the traffic patterns can change rapidly or the data centers have a large size. To overcome these limitations, this paper proposes a novel distributed approach called eAware that dynamically idles a port or a switch to save energy by examining the queue lengths and utilizations at switch ports. Through extensive simulations in ns-2, we compare eAware with an existing energy oblivious approach, showing that eAware can save 30%–50% on the total energy consumption by switches in data centers, and only increases the average end-to-end delay of packets by 3%–20% and the packet loss ratio by 0%–0.9%.
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paper_title: Energy Aware Network Operations

paper_content:

Networking devices today consume a non-trivial amount of energy and it has been shown that this energy consumption is largely independent of the load through the devices. With a strong need to curtail the rising operational costs of IT infrastructure, there is a tremendous opportunity for introducing energy awareness in the design and operation of enterprise and data center networks. We focus on these networks as they are under the control of a single administrative domain in which network-wide control can be consistently applied. In this paper, we describe and analyze three approaches to saving energy in single administrative domain networks, without significantly impacting the networks' ability to provide the expected levels of performance and availability. We also explore the trade-offs between conserving energy and meeting performance and availability requirements. We conduct an extensive case study of our algorithms by simulating a real Web 2.0 workload in a real data center network topology using power characterizations that we obtain from real network hardware. Our results indicate that for our workload and data center scenario, 16% power savings (with no performance penalty and small decrease in availability) can be obtained merely by appropriately adjusting the active network elements (links). Significant additional savings (up to 75%) can be obtained by incorporating network traffic management and server workload consolidation.
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Title: Energy-Efficient Networking Solutions in Cloud-Based Environments: A Systematic Literature Review

Section 1: INTRODUCTION
Description 1: This section introduces the importance of energy efficiency in cloud-based environments and provides an overview of the paper's focus on networking components' energy efficiency.

Section 2: RELATED WORK
Description 2: This section discusses previous studies and surveys relevant to energy-efficient solutions in various domains, especially in cloud-based environments.

Section 3: SYSTEMATIC LITERATURE REVIEW
Description 3: This section describes the systematic literature review methodology used in this research, including the definition of the research question, search strategy, study selection, and primary studies management.

Section 4: DATA ANALYSIS
Description 4: This section explains the data analysis methods used in this research, including coding and metamodel creation based on the primary studies.

Section 5: RESULTS
Description 5: This section presents the findings from the primary studies, categorized into strategies, scales, solutions, technologies, and energy efficiency evaluation.

Section 6: DISCUSSION
Description 6: This section discusses the trends and insights derived from the results, highlighting the evolution of energy-efficient networking solutions over time.

Section 7: THREATS TO VALIDITY
Description 7: This section outlines potential threats to the validity of the study's findings and the measures taken to address them.

Section 8: EMERGING RESEARCH DIRECTIONS
Description 8: This section identifies future research challenges and opportunities in the field of energy-efficient networking solutions in cloud-based environments.

Section 9: CONCLUSION
Description 9: This section summarizes the key findings of the literature review and provides concluding remarks on the state of the art in energy-efficient networking solutions.