Fog Computing for Sustainable Smart Cities: A Survey
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paper_title: The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

paper_content:

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as Radio frequency identifications, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organizations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. Based on the application domain, we classify and discuss these solutions under five different categories: 1) smart wearable; 2) smart home; 3) smart city; 4) smart environment; and 5) smart enterprise. This survey is intended to serve as a guideline and a conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.
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paper_title: Data to decision: pushing situational information needs to the edge of the network

paper_content:

Obtaining a high level of situation awareness while maintaining optimal utilization of resources is becoming increasingly important, especially in the context of asymmetric warfare, where information superiority is crucial for maintaining the edge over the opponent. Obtaining an adequate level of situational information from an ISR system is dependent on sensor capabilities as well as the ability to cue the sensors appropriately based on the current information needs and the ability to utilize the collected data with suitable data processing methods. Applying the Data to Decision approach for managing the behavior of sensor systems facilitates optimal use of sensor assets while providing the required level of situational information. The approach presented in the paper combines the Data to Decision approach with the Fog Computing paradigm, where the computation is pushed to the edge of the network. This allows to take advantage of Big Data potentially generated by the sensor systems while keeping the resource requirements in terms of bandwidth manageable. We suggest a System of Systems approach for assembling the ISR system, where individual systems have a high level of autonomy and the computational resources to perform the necessary computation tasks. To facilitate a composition of a System of Systems of sensors for tactical applications the proactive middleware ProWare is applied. The work presented in the paper has been conducted as part of the European Defense Agency project IN4STARS, in the context of which an implementation of a sensor solution is being built, which facilitates on-line sensor cueing and collaboration between sensors by building upon the Fog Computing paradigm and utilizing the Data to Decision concepts.
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paper_title: Fog computing and its role in the internet of things

paper_content:

Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are: a) Low latency and location awareness; b) Wide-spread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of wireless access, f) Strong presence of streaming and real time applications, g) Heterogeneity. In this paper we argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).
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paper_title: Security and Privacy Issues of Fog Computing: A Survey

paper_content:

Fog computing is a promising computing paradigm that extends cloud computing to the edge of networks. Similar to cloud computing but with distinct characteristics, fog computing faces new security and privacy challenges besides those inherited from cloud computing. In this paper, we have surveyed these challenges and corresponding solutions in a brief manner.
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paper_title: Fog computing and its role in the internet of things

paper_content:

Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are: a) Low latency and location awareness; b) Wide-spread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of wireless access, f) Strong presence of streaming and real time applications, g) Heterogeneity. In this paper we argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).
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paper_title: Fog Networking: An Overview on Research Opportunities

paper_content:

The past 15 years have seen the rise of the Cloud, along with rapid increase in Internet backbone traffic and more sophisticated cellular core networks. There are three different types of Clouds: (1) data center, (2) backbone IP network and (3) cellular core network, responsible for computation, storage, communication and network management. Now the functions of these three types of Clouds are descending to be among or near the end users, i.e., to the edge of networks, as Fog. This article presents an overview on research opportunities of Fog networking: an architecture that users one or a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of storage, communication and management. Architecture allocates functionalities, while engineering artifacts that may use a Fog architecture include 5G, home/personal networking, and the Internet of Things.
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paper_title: The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

paper_content:

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as Radio frequency identifications, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organizations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. Based on the application domain, we classify and discuss these solutions under five different categories: 1) smart wearable; 2) smart home; 3) smart city; 4) smart environment; and 5) smart enterprise. This survey is intended to serve as a guideline and a conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.
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paper_title: The Fog Computing Paradigm: Scenarios and Security Issues

paper_content:

Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. In this article, we elaborate the motivation and advantages of Fog computing, and analyse its applications in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks. We discuss the state-of-the-art of Fog computing and similar work under the same umbrella. Security and privacy issues are further disclosed according to current Fog computing paradigm. As an example, we study a typical attack, man-in-the-middle attack, for the discussion of security in Fog computing. We investigate the stealthy features of this attack by examining its CPU and memory consumption on Fog device.
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paper_title: Data to decision: pushing situational information needs to the edge of the network

paper_content:

Obtaining a high level of situation awareness while maintaining optimal utilization of resources is becoming increasingly important, especially in the context of asymmetric warfare, where information superiority is crucial for maintaining the edge over the opponent. Obtaining an adequate level of situational information from an ISR system is dependent on sensor capabilities as well as the ability to cue the sensors appropriately based on the current information needs and the ability to utilize the collected data with suitable data processing methods. Applying the Data to Decision approach for managing the behavior of sensor systems facilitates optimal use of sensor assets while providing the required level of situational information. The approach presented in the paper combines the Data to Decision approach with the Fog Computing paradigm, where the computation is pushed to the edge of the network. This allows to take advantage of Big Data potentially generated by the sensor systems while keeping the resource requirements in terms of bandwidth manageable. We suggest a System of Systems approach for assembling the ISR system, where individual systems have a high level of autonomy and the computational resources to perform the necessary computation tasks. To facilitate a composition of a System of Systems of sensors for tactical applications the proactive middleware ProWare is applied. The work presented in the paper has been conducted as part of the European Defense Agency project IN4STARS, in the context of which an implementation of a sensor solution is being built, which facilitates on-line sensor cueing and collaboration between sensors by building upon the Fog Computing paradigm and utilizing the Data to Decision concepts.
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paper_title: Reliability in the utility computing era: Towards reliable Fog computing

paper_content:

This paper considers current paradigms in computing and outlines the most important aspects concerning their reliability. The Fog computing paradigm as a non-trivial extension of the Cloud is considered and the reliability of the networks of smart devices are discussed. Combining the reliability requirements of grid and cloud paradigms with the reliability requirements of networks of sensor and actuators it follows that designing a reliable Fog computing platform is feasible.
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paper_title: Fog Networking: An Overview on Research Opportunities

paper_content:

The past 15 years have seen the rise of the Cloud, along with rapid increase in Internet backbone traffic and more sophisticated cellular core networks. There are three different types of Clouds: (1) data center, (2) backbone IP network and (3) cellular core network, responsible for computation, storage, communication and network management. Now the functions of these three types of Clouds are descending to be among or near the end users, i.e., to the edge of networks, as Fog. This article presents an overview on research opportunities of Fog networking: an architecture that users one or a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of storage, communication and management. Architecture allocates functionalities, while engineering artifacts that may use a Fog architecture include 5G, home/personal networking, and the Internet of Things.
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paper_title: Key ingredients in an IoT recipe: Fog Computing, Cloud computing, and more Fog Computing

paper_content:

This paper examines some of the most promising and challenging scenarios in IoT, and shows why current compute and storage models confined to data centers will not be able to meet the requirements of many of the applications foreseen for those scenarios. Our analysis is particularly centered on three interrelated requirements: 1) mobility; 2) reliable control and actuation; and 3) scalability, especially, in IoT scenarios that span large geographical areas and require real-time decisions based on data analytics. Based on our analysis, we expose the reasons why Fog Computing is the natural platform for IoT, and discuss the unavoidable interplay of the Fog and the Cloud in the coming years. In the process, we review some of the technologies that will require considerable advances in order to support the applications that the IoT market will demand.
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paper_title: Energy Efficient Location and Activity-aware On-Demand Mobile Distributed Sensing Platform for Sensing as a Service in IoT Clouds

paper_content:

The Internet of Things (IoT) envisions billions of sensors deployed around us and connected to the Internet, where the mobile crowd sensing technologies are widely used to collect data in different contexts of the IoT paradigm. Due to the popularity of Big Data technologies, processing and storing large volumes of data have become easier than ever. However, large-scale data management tasks still require significant amounts of resources that can be expensive regardless of whether they are purchased or rented (e.g., pay-as-you-go infrastructure). Further, not everyone is interested in such large-scale data collection and analysis. More importantly, not everyone has the financial and computational resources to deal with such large volumes of data. Therefore, a timely need exists for a cloud-integrated mobile crowd sensing platform that is capable of capturing sensors data, on-demand, based on conditions enforced by the data consumers. In this paper, we propose a context-aware, specifically, location and activity-aware mobile sensing platform called context-aware mobile sensor data engine (C-MOSDEN) for the IoT domain. We evaluated the proposed platform using three real-world scenarios that highlight the importance of selective sensing . The computational effectiveness and efficiency of the proposed platform are investigated and are used to highlight the advantages of context-aware selective sensing.
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paper_title: Fog computing and its role in the internet of things

paper_content:

Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are: a) Low latency and location awareness; b) Wide-spread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of wireless access, f) Strong presence of streaming and real time applications, g) Heterogeneity. In this paper we argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).
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paper_title: Energy harvesting technologies for low-power electronics

paper_content:

Power consumption is one of the most critical issues when designing low-cost electronic devices, such as sensing nodes in wireless sensor networks. To support their operation, such systems usually contain a battery; however, when the battery has consumed all its energy, the node (e.g. the sensor) must be retrieved and the battery replaced. If the node is located in a remote and non-accessible placement, battery replacement can become an expensive (and even impossible) task. This way, energy harvesting has emerged as a suitable alternative to supply low-power electronic systems, by converting ambient energy into electric power. Scavenged energy can be used to directly supply the circuits, or stored to be used when needed. This paper summarises the power needs of a general wireless sensor node and describes the main principles of most representative energy harvesting technologies. Copyright © 2012 John Wiley & Sons, Ltd.
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paper_title: OpenWSN: a standards‐based low‐power wireless development environment

paper_content:

The OpenWSN project is an open-source implementation of a fully standards-based protocol stack for capillary networks, rooted in the new IEEE802.15.4e Time Synchronized Channel Hopping standard. IEEE802.15.4e, coupled with Internet of Things standards, such as 6LoWPAN, RPL and CoAP, enables ultra-low-power and highly reliable mesh networks, which are fully integrated into the Internet. The resulting protocol stack will be cornerstone to the upcoming machine-to-machine revolution. ::: ::: This article gives an overview of the protocol stack, as well as key integration details and the platforms and tools developed around it. The pure-C OpenWSN stack was ported to four off-the-shelf platforms representative of hardware currently used, from older 16-bit microcontroller to state-of-the-art 32-bit Cortex-M architectures. The tools developed around the low-power mesh networks include visualisation and debugging software, a simulator to mimic OpenWSN networks on a PC, and the environment needed to connect those networks to the Internet. ::: ::: Experimental results presented in this article include a network where motes operate at an average radio duty cycle well below 0.1% and an average current draw of 68 μA on off-the-shelf hardware. These ultra-low-power requirements enable a range of applications, with motes perpetually powered by micro-scavenging devices. OpenWSN is, to the best of our knowledge, the first open-source implementation of the IEEE802.15.4e standard. Copyright © 2012 John Wiley & Sons, Ltd.
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paper_title: Augmented Brain Computer Interaction Based on Fog Computing and Linked Data

paper_content:

An augmented brain computer interface that can detect users' brain states in real-life situations has been developed using wireless EEG headsets, smart phones and ubiquitous computing services. This kind of wearable natural user interfaces will have a wide-range of potential applications in future smart environments. This paper describes its ubiquitous system architecture and introduces its enabling technologies, which include machine-to-machine publish/subscribe protocols, multi-tier fog/cloud computing infrastructure and a linked data web. Its real-time responsiveness and easiness-of-use will be demonstrated by playing a multi-player on-line BCI game EEG Tractor Beam at the Intelligent Environment Conference.
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paper_title: Energy Efficient Location and Activity-aware On-Demand Mobile Distributed Sensing Platform for Sensing as a Service in IoT Clouds

paper_content:

The Internet of Things (IoT) envisions billions of sensors deployed around us and connected to the Internet, where the mobile crowd sensing technologies are widely used to collect data in different contexts of the IoT paradigm. Due to the popularity of Big Data technologies, processing and storing large volumes of data have become easier than ever. However, large-scale data management tasks still require significant amounts of resources that can be expensive regardless of whether they are purchased or rented (e.g., pay-as-you-go infrastructure). Further, not everyone is interested in such large-scale data collection and analysis. More importantly, not everyone has the financial and computational resources to deal with such large volumes of data. Therefore, a timely need exists for a cloud-integrated mobile crowd sensing platform that is capable of capturing sensors data, on-demand, based on conditions enforced by the data consumers. In this paper, we propose a context-aware, specifically, location and activity-aware mobile sensing platform called context-aware mobile sensor data engine (C-MOSDEN) for the IoT domain. We evaluated the proposed platform using three real-world scenarios that highlight the importance of selective sensing . The computational effectiveness and efficiency of the proposed platform are investigated and are used to highlight the advantages of context-aware selective sensing.
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paper_title: A Survey of the Semantic Specification of Sensors

paper_content:

Semantic sensor networks use declarative descriptions of sensors promote reuse and integration, and to help solve the difficulties of installing, querying and maintaining complex, heterogeneous sensor networks. This paper reviews the state of the art for the semantic specification of sensors, one of the fundamental technologies in the semantic sensor network vision. Twelve sensor ontologies are reviewed and analysed for the range and expressive power of their concepts. The reasoning and search technology developed in conjunction with these ontologies is also reviewed, as is technology for annotating OGC standards with links to ontologies. Sensor concepts that cannot be expressed accurately by current sensor ontologies are also discussed.
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paper_title: CroCo: Ontology-Based, Cross-Application Context Management

paper_content:

Context-awareness is a key issue for future applications within heterogeneous and networked environments. In terms of efficiency and reusability, such applications should be separated from the problems of context gathering and modeling, but should instead profit from and contribute to cross-application context information. For this purpose, an ontology-based, cross-application context modeling and management service is needed to provide appropriate support for the variety of conceivable application scenarios. Although there have been numerous approaches dealing with application-independent context management, none of them sufficiently supports the vision of cross-application context handling. Therefore, we present CroCo, an ontology-based context management service that allows for cross-application context gathering, modeling, and provision. We verified and tested the practicability of our concept within two different projects with disparate application scenarios.
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paper_title: Improving Web Sites Performance Using Edge Servers in Fog Computing Architecture

paper_content:

In this paper, we consider web optimization within Fog Computing context. We apply existing methods for web optimization in a novel manner, such that these methods can be combined with unique knowledge that is only available at the edge (Fog) nodes. More dynamic adaptation to the user's conditions (eg. network status and device's computing load) can also be accomplished with network edge specific knowledge. As a result, a user's web page rendering performance is improved beyond that achieved by simply applying those methods at the web server or CDNs.
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paper_title: WiFi: what's next?

paper_content:

WiFi, also known as 802.11b, has become the preferred technology for wireless local area networking in both business and home environments. Even though it was designed primarily for private applications, WiFi is also being deployed in public places to create so-called hotspots, where WiFi-capable users can obtain broadband Internet access. This new domain of application could be the major future market opportunity for WiFi, but in order to take advantage of it, several key challenges, both technical and business-related, must be overcome. We outline these challenges and discuss approaches to solutions.
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paper_title: An Overview on Wireless Sensor Networks Technology and Evolution

paper_content:

Wireless sensor networks (WSNs) enable new applications and require non-conventional paradigms for protocol design due to several constraints. Owing to the requirement for low device complexity together with low energy consumption (i.e., long network lifetime), a proper balance between communication and signal/data processing capabilities must be found. This motivates a huge effort in research activities, standardization process, and industrial investments on this field since the last decade. This survey paper aims at reporting an overview of WSNs technologies, main applications and standards, features in WSNs design, and evolutions. In particular, some peculiar applications, such as those based on environmental monitoring, are discussed and design strategies highlighted; a case study based on a real implementation is also reported. Trends and possible evolutions are traced. Emphasis is given to the IEEE 802.15.4 technology, which enables many applications of WSNs. Some example of performance characteristics of 802.15.4-based networks are shown and discussed as a function of the size of the WSN and the data type to be exchanged among nodes.
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paper_title: Demystifying 802.11n power consumption

paper_content:

We report what we believe to be the first measurements of the power consumption of an 802.11n NIC across a broad set of operating states (channel width, transmit power, rates, antennas, MIMO streams, sleep, and active modes). We find the popular practice of racing to sleep (by sending data at the highest possible rate) to be a useful heuristic to save energy, but that it does not always hold. We contribute three other useful heuristics: wide channels are an energy-efficient way to increase rates; multiple RF chains are more energy-efficient only when the channel is good enough to support the highest MIMO rates; and single antenna operation is always most energy-efficient for short packets
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paper_title: Power consumption analysis of Bluetooth Low Energy, ZigBee and ANT sensor nodes in a cyclic sleep scenario

paper_content:

This paper is intended to guide developers of wireless systems who are puzzled by the vast number of radio configuration parameters and options. We provide experimental data comparing power consumption of Bluetooth Low Energy (BLE), ZigBee and ANT protocols for a cyclic sleep scenario, in which a short-range and low-power wireless sensor node periodically sends a data packet to a remote `hub' with intervening sleep intervals. Devices such as wearable health monitors often use this scenario when interfacing with a mobile phone-based hub. For all measured sleep intervals BLE achieved lower power consumption (10.1 uA, 3.3 V supply at 120 s interval), compared with ZigBee (15.7 uA), and ANT (28.2 uA). Most of the power consumption differences can be attributed to the time taken for a node to connect to the hub after waking up and the use of sleep between individual RF packets. For the three protocols we determined a sleep interval at which the tradeoff between power consumption and data rate is optimized.
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paper_title: The Analysis of 6LowPAN Technology

paper_content:

IPv6 over IEEE802.15.4 (a.k.a. 6LowPAN), has become the standard for low-rate wireless personal area networks (LR-WPAN). IPv6 is taken as an interconnection scheme for IEEE802.15.4 equipments at network layer, 6LowPAN technology has attracted extensive attention. This paper introduced IEEE802.15.4 standard and 6LowPAN technology, discussed 6LowPAN's advantages, analyzed its key technologies, and the applications of 6LowPAN were explored.
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paper_title: Achilles and the tortoise: Power consumption in IEEE 802.11n and IEEE 802.11g networks

paper_content:

Cloud computing is currently emerging as the de facto standard for Internet service provisioning. This uptake is motivated, among other aspects, by the significant reduction in energy consumption that can be achieved by centralizing, consolidating and optimizing large IT infrastructures. At the same time, however, users expect to access cloud services via wireless access networks using smartphones and tablets. Several studies already show that wireless technologies such as WiFi and 4G are becoming the dominant access to cloud services. However, while energy efficiency is accounted for the end-user devices and data-centers, the actual energy consumption of wireless access networks is typically overlooked, even though it is expected to account for about 90 % of the entire wireless cloud energy footprint. In this paper, we use real-world measurements to present a complete analysis of the power consumption and performance of IEEE 802.11n. We also compare IEEE 802.11n with its predecessor, the widely deployed IEEE 802.11g standard, and confirm that 802.11n (2×2 MIMO) performs ~ 4.5 times better than 802.11g in terms of maximum network throughput as expected while at the same time reducing the required energy per bit by ~ 50%.
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paper_title: Applying Seamful Design in Location-Based Mobile Museum Applications

paper_content:

The application of mobile computing is currently altering patterns of our behavior to a greater degree than perhaps any other invention. In combination with the introduction of power efficient wireless communication technologies, such as Bluetooth Low Energy (BLE), designers are today increasingly empowered to shape the way we interact with our physical surroundings and thus build entirely new experiences. However, our evaluations of BLE and its abilities to facilitate mobile location-based experiences in public environments revealed a number of potential problems. Most notably, the position and orientation of the user in combination with various environmental factors, such as crowds of people traversing the space, were found to cause major fluctuations of the received BLE signal strength. These issues are rendering a seamless functioning of any location-based application practically impossible. Instead of achieving seamlessness by eliminating these technical issues, we thus choose to advocate the use of a seamful approach, i.e. to reveal and exploit these problems and turn them into a part of the actual experience. In order to demonstrate the viability of this approach, we designed, implemented and evaluated the Ghost Detector - an educational location-based museum game for children. By presenting a qualitative evaluation of this game and by motivating our design decisions, this paper provides insight into some of the challenges and possible solutions connected to the process of developing location-based BLE-enabled experiences for public cultural spaces.
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paper_title: Wimax Technology for Broadband Wireless Access

paper_content:

WiMAX Broadband Wireless Access Technology, based on the IEEE 802.16 standard, is at the origin of great promises for many different markets covering fixed wireless Internet Access, Backhauling and Mobile cellular networks. WiMAX technology is designed for the transmission of multimedia services (voice, Internet, email, games and others) at high data rates (of the order of Mb/s per user). It is a very powerful but sometimes complicated technique. The WiMAX System is described in thousands of pages of IEEE 802.16 standard and amendments documents and WiMAX Forum documents. WiMAX: Technology for Broadband Wireless Access provides a global picture of WiMAX and a large number of details that makes access to WiMAX documents much easier. All the aspects of WIMAX are covered. Illustrations and clear explanations for all the main procedures of WiMAX are pedagogically presented in a succession of relatively short chapters Topics covered include WiMAX genesis and framework, WiMAX topologies, protocol layers, MAC layer, MAC frames, WiMAX multiple access, the physical layer, QoS Management, Radio Resource Management, Bandwidth allocation, Network Architecture, Mobility and Security Features a glossary of abbreviations and their definitions, and a wealth of explanatory tables and figures Highlights the most recent changes, including the 802.16e amendment of the standard, needed for Mobile WiMAX Includes technical comparisons of WiMAX vs. 802.11 (WiFi) and cellular 3G technologies This technical introduction to WiMAX, explaining the rather complex standards (IEEE 802.16-2004 and 802.16e) is a must read for engineers, decision-makers and students interested in WiMAX, as well as other researchers and scientists from this evolving field.
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paper_title: Long-Range IoT Technologies: The Dawn of LoRa™

paper_content:

The last years have seen the widespread diffusion of novel Low Power Wide Area Network (LPWAN) technologies, which are gaining momentum and commercial interest as enabling technologies for the Internet of Things. In this paper we discuss some of the most interesting LPWAN solutions, focusing in particular on LoRa™, one of the last born and most promising technologies for the wide-area IoT.
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paper_title: Near field communication

paper_content:

For many years, pervasive computing research has explored the potential benefits of creating a connection between the virtual world of the Internet, and the physical world we live in. The Near Field Communication (NFC) standard might, at last, be the technology that makes this vision-sometimes referred to as the Internet of things-a ubiquitous reality.
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paper_title: Group Communication for the Constrained Application Protocol (CoAP)

paper_content:

The Constrained Application Protocol (CoAP) is a specialized web ::: transfer protocol for constrained devices and constrained networks. It ::: is anticipated that constrained devices will often naturally operate ::: in groups (e.g., in a building automation scenario, all lights in a ::: given room may need to be switched on/off as a group). This ::: specification defines how CoAP should be used in a group communication ::: context. An approach for using CoAP on top of IP multicast is detailed ::: based on existing CoAP functionality as well as new features ::: introduced in this specification. Also, various use cases and ::: corresponding protocol flows are provided to illustrate important ::: concepts. Finally, guidance is provided for deployment in various ::: network topologies.
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paper_title: Performance evaluation of MQTT and CoAP via a common middleware

paper_content:

Wireless sensor networks (WSNs) typically consist of sensor nodes and gateways that operate on devices with limited resources. As a result, WSNs require bandwidth-efficient and energy-efficient application protocols for data transmission. Message Queue Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) are two such protocols proposed for resource-constrained devices. In this paper, we design and implement a common middleware that supports MQTT and CoAP and provides a common programming interface. We design the middleware to be extensible to support future protocols. Using the common middleware, we conducted experiments to study the performance of MQTT and CoAP in terms of end-to-end delay and bandwidth consumption. Experimental results reveal that MQTT messages have lower delay than CoAP messages at lower packet loss rates and higher delay than CoAP messages at higher loss rates. Moreover, when the message size is small and the loss rate is equal to or less than 25%, CoAP generates lower additional traffic than MQTT to ensure message reliability.
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paper_title: Advanced Message Queuing Protocol

paper_content:

The advanced message queuing protocol (AMQP) working group's goal is to create an open standard for an interoperable enterprise-scale asynchronous messaging protocol. AMQP is finally addressing the lack of enterprise messaging interoperability standards. This relatively simple yet compellingly powerful enterprise messaging protocol is thus poised to open up a bright new era for enterprise messaging
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paper_title: CoAP: An Application Protocol for Billions of Tiny Internet Nodes

paper_content:

The Constrained Application Protocol (CoAP) is a transfer protocol for constrained nodes and networks, such as those that will form the Internet of Things. Much like its older and heavier cousin HTTP, CoAP uses the REST architectural style. Based on UDP and unencumbered by historical baggage, however, CoAP aims to achieve its modest goals with considerably less complexity.
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paper_title: The Constrained Application Protocol (CoAP)

paper_content:

The Constrained Application Protocol (CoAP) is a specialized web ::: transfer protocol for use with constrained nodes and constrained ::: (e.g., low-power, lossy) networks. The nodes often have 8-bit ::: microcontrollers with small amounts of ROM and RAM, while constrained ::: networks such as IPv6 over Low-Power Wireless Personal Area Networks ::: (6LoWPANs) often have high packet error rates and a typical throughput ::: of 10s of kbit/s. The protocol is designed for machine- to-machine ::: (M2M) applications such as smart energy and building automation. CoAP ::: provides a request/response interaction model between application ::: endpoints, supports built-in discovery of services and resources, and ::: includes key concepts of the Web such as URIs and Internet media ::: types. CoAP is designed to easily interface with HTTP for integration ::: with the Web while meeting specialized requirements such as multicast ::: support, very low overhead, and simplicity for constrained ::: environments.
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paper_title: MQTT-S — A publish/subscribe protocol for Wireless Sensor Networks

paper_content:

Wireless sensor networks (WSNs) pose novel challenges compared with traditional networks. To answer such challenges a new communication paradigm, data-centric communication, is emerging. One form of data-centric communication is the publish/subscribe messaging system. Compared with other data-centric variants, publish/subscribe systems are common and wide-spread in distributed computing. Thus, extending publish/subscribe systems intoWSNs will simplify the integration of sensor applications with other distributed applications. This paper describes MQTT-S [1], an extension of the open publish/subscribe protocol message queuing telemetry transport (MQTT) [2] to WSNs. MQTT-S is designed in such a way that it can be run on low-end and battery-operated sensor/actuator devices and operate over bandwidth-constraint WSNs such as ZigBee-based networks. Various protocol design points are discussed and compared. MQTT-S has been implemented and is currently being tested on the IBM wireless sensor networking testbed [3]. Implementation aspects, open challenges and future work are also presented.
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paper_title: Lithe: Lightweight Secure CoAP for the Internet of Things

paper_content:

The Internet of Things (IoT) enables a wide range of application scenarios with potentially critical actuating and sensing tasks, e.g., in the e-health domain. For communication at the application layer, resource-constrained devices are expected to employ the constrained application protocol (CoAP) that is currently being standardized at the Internet Engineering Task Force. To protect the transmission of sensitive information, secure CoAP mandates the use of datagram transport layer security (DTLS) as the underlying security protocol for authenticated and confidential communication. DTLS, however, was originally designed for comparably powerful devices that are interconnected via reliable, high-bandwidth links. In this paper, we present Lithe-an integration of DTLS and CoAP for the IoT. With Lithe, we additionally propose a novel DTLS header compression scheme that aims to significantly reduce the energy consumption by leveraging the 6LoWPAN standard. Most importantly, our proposed DTLS header compression scheme does not compromise the end-to-end security properties provided by DTLS. Simultaneously, it considerably reduces the number of transmitted bytes while maintaining DTLS standard compliance. We evaluate our approach based on a DTLS implementation for the Contiki operating system. Our evaluation results show significant gains in terms of packet size, energy consumption, processing time, and network-wide response times when compressed DTLS is enabled.
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paper_title: Semantic-based IoT device discovery and recommendation mechanism

paper_content:

The Internet of Things is about data, different devices from different places and the connectivity between them. Our goal is to find a way to interact with the devices and their data, according to the customer's requirements, in the IoT context, all this supported by the use of Web services. We present a broker based architecture for service selection which facilitates devices to specify both functional and non-functional requirements. We develop a device discovery and recommendation mechanism based on a proposed web service similarity metric.
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paper_title: Neighbor Discovery for Opportunistic Networking in Internet of Things Scenarios: A Survey

paper_content:

Neighbor discovery was initially conceived as a means to deal with energy issues at deployment, where the main objective was to acquire information about network topology for subsequent communication. Nevertheless, over recent years, it has been facing new challenges due to the introduction of mobility of nodes over static networks mainly caused by the opportunistic presence of nodes in such a scenario. The focus of discovery has, therefore, shifted toward more challenging environments, where connectivity opportunities need to be exploited for achieving communication. In fact, discovery has traditionally been focused on tradeoffs between energy and latency in order to reach an overlapping of communication times between neighboring nodes. With the introduction of opportunistic networking, neighbor discovery has instead aimed toward the more challenging problem of acquiring knowledge about the patterns of encounters between nodes. Many Internet of Things applications (e.g., smart cities) can, in fact, benefit from such discovery, since end-to-end paths may not directly exist between sources and sinks of data, thus requiring the discovery and exploitation of rare and short connectivity opportunities to relay data. While many of the older discovery approaches are still valid, they are not entirely designed to exploit the properties of these new challenging scenarios. A recent direction in research is, therefore, to learn and exploit knowledge about mobility patterns to improve the efficiency in the discovery process. In this paper, a new classification and taxonomy is presented with an emphasis on recent protocols and advances in this area, summarizing issues and ways for potential improvements. As we will show, knowledge integration in the process of neighbor discovery leads to a more efficient scheduling of the resources when contacts are expected, thus allowing for faster discovery, while, at the same time allowing for energy savings when such contacts are not expected.
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paper_title: Key ingredients in an IoT recipe: Fog Computing, Cloud computing, and more Fog Computing

paper_content:

This paper examines some of the most promising and challenging scenarios in IoT, and shows why current compute and storage models confined to data centers will not be able to meet the requirements of many of the applications foreseen for those scenarios. Our analysis is particularly centered on three interrelated requirements: 1) mobility; 2) reliable control and actuation; and 3) scalability, especially, in IoT scenarios that span large geographical areas and require real-time decisions based on data analytics. Based on our analysis, we expose the reasons why Fog Computing is the natural platform for IoT, and discuss the unavoidable interplay of the Fog and the Cloud in the coming years. In the process, we review some of the technologies that will require considerable advances in order to support the applications that the IoT market will demand.
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paper_title: Cloudrone: Micro Clouds in the Sky

paper_content:

This paper presents Cloudrone- a preliminary idea of deploying a lightweight micro cloud infrastructure in the sky using indigenously built low cost drones, single board computers and lightweight Operating System virtualization technologies. Our paper lays out the preliminary ideas on such a system that can be instantaneously deployed on demand. We describe an initial design of Cloudrone and provide a preliminary evaluation of the proposed system mainly focussed on the scalability issues of supporting multiple services and users.
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paper_title: Leveraging proximity services for relay device discovery in user-provided IoT networks

paper_content:

Since installing cellular interfaces on a huge number of Internet of Things (IoT) devices is expensive, we propose to use a user equipment (UE) with a local wireless interface as a mobile IoT gateway for fixed IoT devices. In this paper, we design a new mobile architecture based on name-based communications. However, due to UEs' mobility and short range of Wi-Fi communication, discovering such an UE, which we call a relay UE, is difficult and a brute discovery incurs large communication overheads. Thus we propose a light-weight relay UE discovery mechanism by leveraging proximity services (ProSe) to achieve low overheads of discovery messages.
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paper_title: A neighbor collaboration mechanism for mobile crowd sensing in opportunistic networks

paper_content:

Data collection from a crowd of mobile devices is an essential building block of emerging mobile sensing systems. In this paper, we propose an efficient information diffusion protocol for sensor data collection via an opportunistic network. The proposed method detects groups of pedestrians based on the history of radio connectivity between the nodes and maintains a local network (i.e., a cluster) among the detected group members. By collaboratively performing neighbor discovery and link management with the cluster members, it enhances energy-efficiency of the neighbor discovery and minimizes the information delivery delay. Simulation results show that the proposed method can improve the message delivery performance by 16%-83% with equivalent contact probing intervals.
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paper_title: The Challenges of Data Quality and Data Quality Assessment in the Big Data Era

paper_content:

High-quality data are the precondition for analyzing and using big data and for guaranteeing the value of the data. Currently, comprehensive analysis and research of quality standards and quality assessment methods for big data are lacking. First, this paper summarizes reviews of data quality research. Second, this paper analyzes the data characteristics of the big data environment, presents quality challenges faced by big data, and formulates a hierarchical data quality framework from the perspective of data users. This framework consists of big data quality dimensions, quality characteristics, and quality indexes. Finally, on the basis of this framework, this paper constructs a dynamic assessment process for data quality. This process has good expansibility and adaptability and can meet the needs of big data quality assessment. The research results enrich the theoretical scope of big data and lay a solid foundation for the future by establishing an assessment model and studying evaluation algorithms.
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paper_title: An Adaptive Bayesian System for Context-Aware Data Fusion in Smart Environments

paper_content:

The adoption of multi-sensor data fusion techniques is essential to effectively merge and analyze heterogeneous data collected by multiple sensors, pervasively deployed in a smart environment. Existing literature leverages contextual information in the fusion process, to increase the accuracy of inference and hence decision making in a dynamically changing environment. In this paper, we propose a context-aware, self-optimizing, adaptive system for sensor data fusion, based on a three-tier architecture. Heterogeneous data collected by sensors at the lowest tier are combined by a dynamic Bayesian network at the intermediate tier, which also integrates contextual information to refine the inference process. At the highest tier, a self-optimization process dynamically reconfigures the sensory infrastructure, by sampling a subset of sensors in order to minimize energy consumption and maximize inference accuracy. A Bayesian approach allows to deal with the imprecision of sensory measurements, due to environmental noise and possible hardware malfunctions. The effectiveness of our approach is demonstrated with the application scenario of the user activity recognition in an Ambient Intelligence system managing a smart home environment. Experimental results show that the proposed solution outperforms static approaches for context-aware multi-sensor fusion, achieving substantial energy savings whilst maintaining a high degree of inference accuracy.
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paper_title: Policy-driven security management for fog computing: Preliminary framework and a case study

paper_content:

With the increasing user demand for elastic provisioning of resources coupled with ubiquitous and on-demand access to data, cloud computing has been recognized as an emerging technology to meet such dynamic user demands. In addition, with the introduction and rising use of mobile devices, the Internet of Things (IoT) has recently received considerable attention since the IoT has brought physical devices and connected them to the Internet, enabling each device to share data with surrounding devices and virtualized technologies in real-time. Consequently, the exploding data usage requires a new, innovative computing platform that can provide robust real-time data analytics and resource provisioning to clients. As a result, fog computing has recently been introduced to provide computation, storage and networking services between the end-users and traditional cloud computing data centers. This paper proposes a policy-based management of resources in fog computing, expanding the current fog computing platform to support secure collaboration and interoperability between different user-requested resources in fog computing.
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paper_title: Understanding and Using Context

paper_content:

Context is a poorly used source of information in our computing environments. As a result, we have an impoverished understanding of what context is and how it can be used. In this paper, we provide an operational definition of context and discuss the different ways in which context can be used by context-aware applications. We also present the Context Toolkit, an architecture that supports the building of these context-aware applications. We discuss the features and abstractions in the toolkit that make the task of building applications easier. Finally, we introduce a new abstraction, a situation which we believe will provide additional support to application designers.
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paper_title: Fog Computing Micro Datacenter Based Dynamic Resource Estimation and Pricing Model for IoT

paper_content:

Pervasive and ubiquitous computing services have recently been under focus of not only the research community, but developers as well. Prevailing wireless sensor networks (WSNs), Internet of Things (IoT), and healthcare related services have made it difficult to handle all the data in an efficient and effective way and create more useful services. Different devices generate different types of data with different frequencies. Therefore, amalgamation of cloud computing with IoTs, termed as Cloud of Things (CoT) has recently been under discussion in research arena. CoT provides ease of management for the growing media content and other data. Besides this, features like: ubiquitous access, service creation, service discovery, and resource provisioning play a significant role, which comes with CoT. Emergency, healthcare, and latency sensitive services require real-time response. Also, it is necessary to decide what type of data is to be uploaded in the cloud, without burdening the core network and the cloud. For this purpose, Fog computing plays an important role. Fog resides between underlying IoTs and the cloud. Its purpose is to manage resources, perform data filtration, preprocessing, and security measures. For this purpose, Fog requires an effective and efficient resource management framework for IoTs, which we provide in this paper. Our model covers the issues of resource prediction, customer type based resource estimation and reservation, advance reservation, and pricing for new and existing IoT customers, on the basis of their characteristics. The implementation was done using Java, while the model was evaluated using CloudSim toolkit. The results and discussion show the validity and performance of our system.
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paper_title: Research on dynamic data fusion algorithm based on context awareness

paper_content:

In traditional data fusion algorithms based on context awareness, time-varying application situations and context acquisition cost are not considered, which leads to inaccurate situation prediction and low applicability of data fusion. In this paper, a space-based context model is introduced, in which the sensors' history from three aspects, the context attribute, the context state and the situation space are described. Then optional attributes with the maximum overall utility are chosen by Dynamic Bayesian Networks. After that, the related situation prediction is obtained through data fusion. A data fusion algorithm CFACA (Context Fusion Algorithm based on Context Awareness) proposed in this paper gives a dynamic data fusion method. In the end, the simulation of this algorithm is discussed and the results show the effectiveness of the CFACA.
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paper_title: Software defined networking-based vehicular Adhoc Network with Fog Computing

paper_content:

Vehicular Adhoc Networks (VANETs) have been attracted a lot of research recent years. Although VANETs are deployed in reality offering several services, the current architecture has been facing many difficulties in deployment and management because of poor connectivity, less scalability, less flexibility and less intelligence. We propose a new VANET architecture called FSDN which combines two emergent computing and network paradigm Software Defined Networking (SDN) and Fog Computing as a prospective solution. SDN-based architecture provides flexibility, scalability, programmability and global knowledge while Fog Computing offers delay-sensitive and location-awareness services which could be satisfy the demands of future VANETs scenarios. We figure out all the SDN-based VANET components as well as their functionality in the system. We also consider the system basic operations in which Fog Computing are leveraged to support surveillance services by taking into account resource manager and Fog orchestration models. The proposed architecture could resolve the main challenges in VANETs by augmenting Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Base Station communications and SDN centralized control while optimizing resources utility and reducing latency by integrating Fog Computing. Two use-cases for non-safety service (data streaming) and safety service (Lane-change assistance) are also presented to illustrate the benefits of our proposed architecture.
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paper_title: THE SEMANTIC WEB AND ITS APPLICATIONS

paper_content:

In this paper, a brief introduction to the concept of the semantic web has been made as well as the idea of using ontologies. The main objective of this project is to implement such an application by relying on the studies conducted. Some of the problems which occurred during the course of realizing the aims are also discussed in this paper.
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paper_title: Semantic annotation and reasoning for sensor data

paper_content:

Developments in (wireless) sensor and actuator networks and the capabilities to manufacture low cost and energy efficient networked embedded devices have lead to considerable interest in adding real world sense to the Internet and the Web. Recent work has raised the idea towards combining the Internet of Things (i.e. real world resources) with semantic Web technologies to design future service and applications for the Web. In this paper we focus on the current developments and discussions on designing Semantic Sensor Web, particularly, we advocate the idea of semantic annotation with the existing authoritative data published on the semantic Web. Through illustrative examples, we demonstrate how rule-based reasoning can be performed over the sensor observation and measurement data and linked data to derive additional or approximate knowledge. Furthermore, we discuss the association between sensor data, the semantic Web, and the social Web which enable construction of context-aware applications and services, and contribute to construction of a networked knowledge framework.
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paper_title: A Graph-Based Cloud Architecture for Big Stream Real-Time Applications in the Internet of Things

paper_content:

The Internet of Things (IoT) will consist of billions of interconnected heterogeneous devices denoted as “smart objects.” Smart objects are generally sensor/actuator-equipped and have constrained resources in terms of: (i) processing capabilities; (ii) available ROM/RAM; and (iii) communication reliability. To meet low-latency requirements, real-time IoT applications must rely on specific architectures designed in order to handle and process gigantic (in terms of number of sources of information and rate of received data) streams of data coming from smart objects. We refer to this smart object-generated data stream as “Big Stream,” in contrast to traditional “Big Data” scenarios, where real-time constraints are not considered. In this paper, we propose a novel Cloud architecture for Big Stream applications that can efficiently handle data coming from deployed smart objects through a graph-based processing platform and deliver processed data to consumer applications with lowest latency.
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paper_title: Infrastructure for Data Processing in Large-Scale Interconnected Sensor Networks

paper_content:

With the price of wireless sensor technologies diminishing rapidly we can expect large numbers of autonomous sensor networks being deployed in the near future. These sensor networks will typically not remain isolated but the need of interconnecting them on the network level to enable integrated data processing will arise, thus realizing the vision of a global "sensor Internet." This requires a flexible middleware layer which abstracts from the underlying, heterogeneous sensor network technologies and supports fast and simple deployment and addition of new platforms, facilitates efficient distributed query processing and combination of sensor data, provides support for sensor mobility, and enables the dynamic adaption of the system configuration during runtime with minimal (zero-programming) effort. This paper describes the global sensor networks (GSN) middleware which addresses these goals. We present GSN's conceptual model, abstractions, and architecture, and demonstrate the efficiency of the implementation through experiments with typical high-load application profiles. The GSN implementation is available from http://gsn.sourceforge.net/.
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paper_title: Adaptive Clustering for Dynamic IoT Data Streams

paper_content:

The emergence of the Internet of Things (IoT) has led to the production of huge volumes of real-world streaming data. We need effective techniques to process IoT data streams and to gain insights and actionable information from realworld ::: observations and measurements. Most existing approaches are application or domain dependent. We propose a method which determines how many different clusters can be found in a stream based on the data distribution. After selecting the number of clusters, we use an online clustering mechanism to cluster the incoming data from the streams. Our approach remains adaptive to drifts by adjusting itself as the data changes. We benchmark our approach against state-of-the-art stream clustering algorithms on data streams with data drift. We show ::: how our method can be applied in a use case scenario involving near real-time traffic data. Our results allow to cluster, label and interpret IoT data streams dynamically according to the data distribution. This enables to adaptively process large volumes of dynamic data online based on the current situation. We show ::: how our method adapts itself to the changes. We demonstrate how the number of clusters in a real-world data stream can be determined by analysing the data distributions.
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paper_title: Fog Computing Micro Datacenter Based Dynamic Resource Estimation and Pricing Model for IoT

paper_content:

Pervasive and ubiquitous computing services have recently been under focus of not only the research community, but developers as well. Prevailing wireless sensor networks (WSNs), Internet of Things (IoT), and healthcare related services have made it difficult to handle all the data in an efficient and effective way and create more useful services. Different devices generate different types of data with different frequencies. Therefore, amalgamation of cloud computing with IoTs, termed as Cloud of Things (CoT) has recently been under discussion in research arena. CoT provides ease of management for the growing media content and other data. Besides this, features like: ubiquitous access, service creation, service discovery, and resource provisioning play a significant role, which comes with CoT. Emergency, healthcare, and latency sensitive services require real-time response. Also, it is necessary to decide what type of data is to be uploaded in the cloud, without burdening the core network and the cloud. For this purpose, Fog computing plays an important role. Fog resides between underlying IoTs and the cloud. Its purpose is to manage resources, perform data filtration, preprocessing, and security measures. For this purpose, Fog requires an effective and efficient resource management framework for IoTs, which we provide in this paper. Our model covers the issues of resource prediction, customer type based resource estimation and reservation, advance reservation, and pricing for new and existing IoT customers, on the basis of their characteristics. The implementation was done using Java, while the model was evaluated using CloudSim toolkit. The results and discussion show the validity and performance of our system.
---
paper_title: A method for obtaining digital signatures and public-key cryptosystems

paper_content:

An encryption method is presented with the novel property that publicly revealing an encryption key does not thereby reveal the corresponding decryption key. This has two important consequences: (1) Couriers or other secure means are not needed to transmit keys, since a message can be enciphered using an encryption key publicly revealed by the intented recipient. Only he can decipher the message, since only he knows the corresponding decryption key. (2) A message can be “signed” using a privately held decryption key. Anyone can verify this signature using the corresponding publicly revealed encryption key. Signatures cannot be forged, and a signer cannot later deny the validity of his signature. This has obvious applications in “electronic mail” and “electronic funds transfer” systems. A message is encrypted by representing it as a number M, raising M to a publicly specified power e, and then taking the remainder when the result is divided by the publicly specified product, n , of two large secret primer numbers p and q. Decryption is similar; only a different, secret, power d is used, where e * d ≡ 1(mod (p - 1) * (q - 1)). The security of the system rests in part on the difficulty of factoring the published divisor, n .
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paper_title: The Fog Computing Paradigm: Scenarios and Security Issues

paper_content:

Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. In this article, we elaborate the motivation and advantages of Fog computing, and analyse its applications in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks. We discuss the state-of-the-art of Fog computing and similar work under the same umbrella. Security and privacy issues are further disclosed according to current Fog computing paradigm. As an example, we study a typical attack, man-in-the-middle attack, for the discussion of security in Fog computing. We investigate the stealthy features of this attack by examining its CPU and memory consumption on Fog device.
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paper_title: Edge Mining the Internet of Things

paper_content:

This paper examines the benefits of edge mining -data mining that takes place on the wireless, battery-powered, and smart sensing devices that sit at the edge points of the Internet of Things. Through local data reduction and transformation, edge mining can quantifiably reduce the number of packets that must be sent, reducing energy usage, and remote storage requirements. In addition, edge mining has the potential to reduce the risk in personal privacy through embedding of information requirements at the sensing point, limiting inappropriate use. The benefits of edge mining are examined with respect to three specific algorithms: linear Spanish inquisition protocol (L-SIP), ClassAct, and bare necessities (BN), which are all instantiations of general SIP. In general, the benefits provided by edge mining are related to the predictability of data streams and availability of precise information requirements; results show that L-SIP typically reduces packet transmission by around 95% (20-fold), BN reduces packet transmission by 99.98% (5000-fold), and ClassAct reduces packet transmission by 99.6% (250-fold). Although energy reduction is not as radical because of other overheads, minimization of these overheads can lead up to a 10-fold battery life extension for L-SIP, for example. These results demonstrate the importance of edge mining to the feasibility of many IoT applications.
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paper_title: Preserving privacy in sensor-fog networks

paper_content:

To address the privacy-utility tradeoff associated with wireless sensor networks in general, and a smart television remote in particular, we study and test usability factors and privacy aspects associated with the current framework models of a TV remote, and port the paradigm of Fog computing to arrive at an optimal solution. A Fog node, being closer to the end-devices not only mitigates the problem of latency but also enables computationally expensive operations, which were earlier possible only at cloud-side. We explore various adversary models, which can potentially compromise our framework and suggest measures to help avoid them.
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paper_title: Big Data Privacy in the Internet of Things Era

paper_content:

Over the last few years, we've seen a plethora of Internet of Things (IoT) solutions, products, and services make their way into the industry's marketplace. All such solutions will capture large amounts of data pertaining to the environment as well as their users. The IoT's objective is to learn more and better serve system users. Some IoT solutions might store data locally on devices ("things"), whereas others might store it in the cloud. The real value of collecting data comes through data processing and aggregation on a large scale, where new knowledge can be extracted. However, such procedures can lead to user privacy issues. This article discusses some of the main challenges of privacy in the IoT as well as opportunities for research and innovation. The authors also introduce some of the ongoing research efforts that address IoT privacy issues.
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paper_title: The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

paper_content:

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as Radio frequency identifications, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organizations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. Based on the application domain, we classify and discuss these solutions under five different categories: 1) smart wearable; 2) smart home; 3) smart city; 4) smart environment; and 5) smart enterprise. This survey is intended to serve as a guideline and a conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.
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paper_title: Key ingredients in an IoT recipe: Fog Computing, Cloud computing, and more Fog Computing

paper_content:

This paper examines some of the most promising and challenging scenarios in IoT, and shows why current compute and storage models confined to data centers will not be able to meet the requirements of many of the applications foreseen for those scenarios. Our analysis is particularly centered on three interrelated requirements: 1) mobility; 2) reliable control and actuation; and 3) scalability, especially, in IoT scenarios that span large geographical areas and require real-time decisions based on data analytics. Based on our analysis, we expose the reasons why Fog Computing is the natural platform for IoT, and discuss the unavoidable interplay of the Fog and the Cloud in the coming years. In the process, we review some of the technologies that will require considerable advances in order to support the applications that the IoT market will demand.
---
paper_title: Policy-driven security management for fog computing: Preliminary framework and a case study

paper_content:

With the increasing user demand for elastic provisioning of resources coupled with ubiquitous and on-demand access to data, cloud computing has been recognized as an emerging technology to meet such dynamic user demands. In addition, with the introduction and rising use of mobile devices, the Internet of Things (IoT) has recently received considerable attention since the IoT has brought physical devices and connected them to the Internet, enabling each device to share data with surrounding devices and virtualized technologies in real-time. Consequently, the exploding data usage requires a new, innovative computing platform that can provide robust real-time data analytics and resource provisioning to clients. As a result, fog computing has recently been introduced to provide computation, storage and networking services between the end-users and traditional cloud computing data centers. This paper proposes a policy-based management of resources in fog computing, expanding the current fog computing platform to support secure collaboration and interoperability between different user-requested resources in fog computing.
---
paper_title: The Fog Balancing: Load Distribution for Small Cell Cloud Computing

paper_content:

In 5G future wireless networks, the (ultra)-dense deployment of radio access points is a key drive for satisfying the increase of traffic demand and improving perceived users' quality. (Ultra)-dense deployment combined with capillary edge cloud, the fog, leads the way for optimization of users' Quality of Experience (QoE) and network performance. In this paper, we focus on improving users' QoE by addressing the issue of load balancing in fog computing. In this paper, we consider the challenging case of multiple users requiring computation offloading, where all requests should be processed by local computation clusters resources. We propose a low complexity small cell clusters establishment and resources management customizable algorithm for fog clustering. Our simulation results show that the proposed algorithm yields high users' satisfaction percentage of a minimum of 90% for up to 4 users per small cell, moderate power consumption, and/or high latency gain.
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paper_title: Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud

paper_content:

Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. We propose a different approach for securing data in the cloud using offensive decoy technology. We monitor data access in the cloud and detect abnormal data access patterns. When unauthorized access is suspected and then verified using challenge questions, we launch a disinformation attack by returning large amounts of decoy information to the attacker. This protects against the misuse of the user's real data. Experiments conducted in a local file setting provide evidence that this approach may provide unprecedented levels of user data security in a Cloud environment.
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paper_title: Data to decision: pushing situational information needs to the edge of the network

paper_content:

Obtaining a high level of situation awareness while maintaining optimal utilization of resources is becoming increasingly important, especially in the context of asymmetric warfare, where information superiority is crucial for maintaining the edge over the opponent. Obtaining an adequate level of situational information from an ISR system is dependent on sensor capabilities as well as the ability to cue the sensors appropriately based on the current information needs and the ability to utilize the collected data with suitable data processing methods. Applying the Data to Decision approach for managing the behavior of sensor systems facilitates optimal use of sensor assets while providing the required level of situational information. The approach presented in the paper combines the Data to Decision approach with the Fog Computing paradigm, where the computation is pushed to the edge of the network. This allows to take advantage of Big Data potentially generated by the sensor systems while keeping the resource requirements in terms of bandwidth manageable. We suggest a System of Systems approach for assembling the ISR system, where individual systems have a high level of autonomy and the computational resources to perform the necessary computation tasks. To facilitate a composition of a System of Systems of sensors for tactical applications the proactive middleware ProWare is applied. The work presented in the paper has been conducted as part of the European Defense Agency project IN4STARS, in the context of which an implementation of a sensor solution is being built, which facilitates on-line sensor cueing and collaboration between sensors by building upon the Fog Computing paradigm and utilizing the Data to Decision concepts.
---
paper_title: Preserving privacy in sensor-fog networks

paper_content:

To address the privacy-utility tradeoff associated with wireless sensor networks in general, and a smart television remote in particular, we study and test usability factors and privacy aspects associated with the current framework models of a TV remote, and port the paradigm of Fog computing to arrive at an optimal solution. A Fog node, being closer to the end-devices not only mitigates the problem of latency but also enables computationally expensive operations, which were earlier possible only at cloud-side. We explore various adversary models, which can potentially compromise our framework and suggest measures to help avoid them.
---
paper_title: Components of fog computing in an industrial internet of things context

paper_content:

The "Internet of Things" (IoT) represents an em- bodiment of the continuous convergence between the physical facet of human activities and its reflection on the informa- tion world. In the context of “Industrial Internet”, where the operation of complex physical machinery is integrated with networked sensors and software applications, IoT is under- stood as a technological enabler of significant advances in the efficiency of industrial processes. In this paper, we elaborate on the main challenges brought on by the Industrial Internet and identify its key enabling technologies relevant to the Fog Computing paradigm. Further on, we propose the introduction of an Adaptive Operations Platform (AOP) to provide end-to- end manageability of the enabling Fog Computing infrastructure according to the operational requirements of industrial process. We present our prototype setup for AOP and elaborate on its performance evaluation in a typical industrial scenario.
---
paper_title: Improving Web Sites Performance Using Edge Servers in Fog Computing Architecture

paper_content:

In this paper, we consider web optimization within Fog Computing context. We apply existing methods for web optimization in a novel manner, such that these methods can be combined with unique knowledge that is only available at the edge (Fog) nodes. More dynamic adaptation to the user's conditions (eg. network status and device's computing load) can also be accomplished with network edge specific knowledge. As a result, a user's web page rendering performance is improved beyond that achieved by simply applying those methods at the web server or CDNs.
---
paper_title: Fog Computing Micro Datacenter Based Dynamic Resource Estimation and Pricing Model for IoT

paper_content:

Pervasive and ubiquitous computing services have recently been under focus of not only the research community, but developers as well. Prevailing wireless sensor networks (WSNs), Internet of Things (IoT), and healthcare related services have made it difficult to handle all the data in an efficient and effective way and create more useful services. Different devices generate different types of data with different frequencies. Therefore, amalgamation of cloud computing with IoTs, termed as Cloud of Things (CoT) has recently been under discussion in research arena. CoT provides ease of management for the growing media content and other data. Besides this, features like: ubiquitous access, service creation, service discovery, and resource provisioning play a significant role, which comes with CoT. Emergency, healthcare, and latency sensitive services require real-time response. Also, it is necessary to decide what type of data is to be uploaded in the cloud, without burdening the core network and the cloud. For this purpose, Fog computing plays an important role. Fog resides between underlying IoTs and the cloud. Its purpose is to manage resources, perform data filtration, preprocessing, and security measures. For this purpose, Fog requires an effective and efficient resource management framework for IoTs, which we provide in this paper. Our model covers the issues of resource prediction, customer type based resource estimation and reservation, advance reservation, and pricing for new and existing IoT customers, on the basis of their characteristics. The implementation was done using Java, while the model was evaluated using CloudSim toolkit. The results and discussion show the validity and performance of our system.
---
paper_title: Smart Cities in Europe

paper_content:

Urban performance currently depends not only on a city's endowment of hard infrastructure (physical capital), but also, and increasingly so, on the availability and quality of knowledge communication and social infrastructure (human and social capital). The latter form of capital is decisive for urban competitiveness. Against this background, the concept of the “smart city” has recently been introduced as a strategic device to encompass modern urban production factors in a common framework and, in particular, to highlight the importance of Information and Communication Technologies (ICTs) in the last 20 years for enhancing the competitive profile of a city. The present paper aims to shed light on the often elusive definition of the concept of the “smart city.” We provide a focused and operational definition of this construct and present consistent evidence on the geography of smart cities in the EU27. Our statistical and graphical analyses exploit in depth, for the first time to our knowledge, the most re...
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Title: Fog Computing for Sustainable Smart Cities: A Survey
Section 1: INTRODUCTION
Description 1: This section introduces the concept of IoT and its growing importance, discusses the challenges of Big Data, and introduces the concept of fog computing as a solution for sustainable smart cities.

Section 2: Main Contributions
Description 2: This section summarizes the contributions and novelty of the article in comparison to previous surveys and studies.

Section 3: FOG COMPUTING: AN OVERVIEW
Description 3: This section provides a detailed overview of fog computing, including its architecture, main characteristics, and advantages over cloud computing.

Section 4: USE CASE SCENARIOS
Description 4: This section presents various use case scenarios where fog computing can be beneficial, including smart agriculture, smart transportation, smart healthcare, smart waste management, smart water management, smart greenhouse gases control, smart power grid, and smart retail store automation.

Section 5: COMMON FEATURES IN FOG COMPUTING
Description 5: This section identifies and discusses the major features required for supporting different types of use cases in smart cities, such as dynamic discovery, device management, multi-protocol support, mobility, context discovery, semantic annotation, data analytics, security, and privacy.

Section 6: EXISTING RESEARCH EFFORTS AND TRENDS
Description 6: This section compares existing research efforts in fog computing, highlighting the most popular features and identifying current trends in the field.

Section 7: LESSONS LEARNED
Description 7: This section discusses how each identified feature contributes towards building sustainable sensing infrastructures for smart cities, along with practical insights and observations.

Section 8: CHALLENGES AND OPPORTUNITIES
Description 8: This section highlights the challenges and opportunities in the development and implementation of fog computing platforms, emphasizing the need for further research and standardization.

Section 9: CONCLUSIONS
Description 9: This section provides a summary of the key findings from the survey, recapitulating the importance of fog computing in building sustainable IoT infrastructure for smart cities and suggesting future directions.