A Review on Failure Node Recovery Algorithms in Wireless Sensor Actor Networks
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paper_title: Wireless Sensor and Actor ∗ Networks: Research Challenges

paper_content:

Abstract Wireless sensor and actor networks (WSANs) refer to a group of sensors and actors linked by wireless medium to perform distributed sensing and acting tasks. The realization of wireless sensor and actor networks (WSANs) needs to satisfy the requirements introduced by the coexistence of sensors and actors. In WSANs, sensors gather information about the physical world, while actors take decisions and then perform appropriate actions upon the environment, which allows a user to effectively sense and act from a distance. In order to provide effective sensing and acting, coordination mechanisms are required among sensors and actors. Moreover, to perform right and timely actions, sensor data must be valid at the time of acting. This paper explores sensor-actor and actor-actor coordination and describes research challenges for coordination and communication problems.
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paper_title: Strategies and Techniques for Node Placement in Wireless Sensor Networks : A Survey

paper_content:

The major challenge in designing wireless sensor networks (WSNs) is the support of the functional, such as data latency, and the non-functional, such as data integrity, requirements while coping with the computation, energy and communication constraints. Careful node placement can be a very effective optimization means for achieving the desired design goals. In this paper, we report on the current state of the research on optimized node placement in WSNs. We highlight the issues, identify the various objectives and enumerate the different models and formulations. We categorize the placement strategies into static and dynamic depending on whether the optimization is performed at the time of deployment or while the network is operational, respectively. We further classify the published techniques based on the role that the node plays in the network and the primary performance objective considered. The paper also highlights open problems in this area of research.
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paper_title: Strategies and Techniques for Node Placement in Wireless Sensor Networks : A Survey

paper_content:

The major challenge in designing wireless sensor networks (WSNs) is the support of the functional, such as data latency, and the non-functional, such as data integrity, requirements while coping with the computation, energy and communication constraints. Careful node placement can be a very effective optimization means for achieving the desired design goals. In this paper, we report on the current state of the research on optimized node placement in WSNs. We highlight the issues, identify the various objectives and enumerate the different models and formulations. We categorize the placement strategies into static and dynamic depending on whether the optimization is performed at the time of deployment or while the network is operational, respectively. We further classify the published techniques based on the role that the node plays in the network and the primary performance objective considered. The paper also highlights open problems in this area of research.
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paper_title: A Localized Self-Healing Algorithm for Networks of Moveable Sensor Nodes

paper_content:

The effectiveness of wireless sensor networks (WSNs) deployed in search and rescue, battlefield reconnaissance, surveillance, and other applications depends on inter-node interaction and maintaining network connectivity. While connectivity can be provisioned at startup, then sustained through careful coordination when nodes move, the network can be partitioned if a node suddenly fails. This paper presents recovery through inward motion (RIM), a distributed algorithm to efficiently restore network connectivity after a node failure. Instead of performing a network-wide analysis to assess the impact of the node failure and set a course of action, RIM triggers a local recovery process by relocating the neighbors of the lost node. RIM minimizes messaging overhead and reduces the distance that individual nodes travel during the recovery. Simulations validate RIM's performance.
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paper_title: Movement-Assisted Connectivity Restoration in Wireless Sensor and Actor Networks

paper_content:

Recent years have witnessed a growing interest in applications of wireless sensor and actor networks (WSANs). In these applications, a set of mobile actor nodes are deployed in addition to sensors in order to collect sensors' data and perform specific tasks in response to detected events/objects. In most scenarios, actors have to respond collectively, which requires interactor coordination. Therefore, maintaining a connected interactor network is critical to the effectiveness of WSANs. However, WSANs often operate unattended in harsh environments where actors can easily fail or get damaged. An actor failure may lead to partitioning the interactor network and thus hinder the fulfillment of the application requirements. In this paper, we present DARA, a distributed actor recovery algorithm, which opts to efficiently restore the connectivity of the interactor network that has been affected by the failure of an actor. Two variants of the algorithm are developed to address 1- and 2-connectivity requirements. The idea is to identify the least set of actors that should be repositioned in order to reestablish a particular level of connectivity. DARA strives to localize the scope of the recovery process and minimize the movement overhead imposed on the involved actors. The effectiveness of DARA is validated through simulation experiments.
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paper_title: A Localized Self-Healing Algorithm for Networks of Moveable Sensor Nodes

paper_content:

The effectiveness of wireless sensor networks (WSNs) deployed in search and rescue, battlefield reconnaissance, surveillance, and other applications depends on inter-node interaction and maintaining network connectivity. While connectivity can be provisioned at startup, then sustained through careful coordination when nodes move, the network can be partitioned if a node suddenly fails. This paper presents recovery through inward motion (RIM), a distributed algorithm to efficiently restore network connectivity after a node failure. Instead of performing a network-wide analysis to assess the impact of the node failure and set a course of action, RIM triggers a local recovery process by relocating the neighbors of the lost node. RIM minimizes messaging overhead and reduces the distance that individual nodes travel during the recovery. Simulations validate RIM's performance.
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Title: A Review on Failure Node Recovery Algorithms in Wireless Sensor Actor Networks

Section 1: INTRODUCTION
Description 1: Introduce Wireless Sensor Actor Networks (WSANs), their importance in applications such as space exploration and battlefield surveillance, and the challenges of maintaining connectivity when actor nodes fail.

Section 2: RELATED WORK
Description 2: Discuss existing schemes for restoring network connectivity in partitioned WSANs, including node replacement and repositioning strategies.

Section 3: NODE RECOVERY ALGORITHMS
Description 3: Present detailed analyses of different node recovery algorithms for WSANs. 

Section 3.1: Recovery through Inward Motion (RIM)
Description 3.1: Explain the RIM algorithm, its process, and how it maintains connectivity by moving neighboring nodes towards the failed node based on 1-hop neighboring information.

Section 3.2: Distributed Actor Recovery Algorithm (DARA)
Description 3.2: Describe the DARA algorithm, its localized approach to restoring connectivity, and detail the DARA-1C and DARA-2C variants.

Section 3.2.1: DARA 1-C
Description 3.2.1: Detail the steps of DARA 1-C, including heartbeat and neighbor list maintenance, failure detection, best candidate selection, and cascaded node relocation.

Section 3.2.2: DARA 2-C
Description 3.2.2: Explain the DARA 2-C algorithm with a focus on 2-connectivity restoration, failure detection, best candidate selection, and node relocation.

Section 3.3: Least Disruptive Topology Repair (LeDiR)
Description 3.3: Describe the LeDiR algorithm, which minimizes node movements and path length extensions by identifying the smallest block and managing the relocation of nodes.

Section 4: COMPARISONS
Description 4: Compare the three algorithms (RIM, DARA, and LeDiR) in terms of recovery overhead, number of relocated nodes, traveled distance, exchanged messages, and impact on path lengths.

Section 5: CONCLUSION
Description 5: Summarize the findings from the review of the three failure node recovery algorithms, highlighting their effectiveness and performance in re-establishing network connectivity in WSANs.