Optimal Mobile Sensor Scheduling for a Guaranteed Coverage Ratio in Hybrid Wireless Sensor Networks

Fu, Zhixin; You, Keyou

doi:10.1155/2013/740841

Cited by 11 publications

(10 citation statements)

References 26 publications

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“…If the target comes in the SR of any MSN, it detects the target. Communication range (CR)/radio range is a radius of MSN in which MSNs can communicate with each other for sharing their location, coordinate, and share information regarding the presence of a target in its SR …”

Section: Proposed Methodsmentioning

confidence: 99%

Distributed Energy Efficient Tracking in Hybrid wireless sensor network (DEETH)

Nighot

Ghatol

Thakare

2017

Int J Communication

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In wireless sensor network (WSN), it is a complex task to track the target when it is moving randomly in an unknown environment. It also becomes difficult to cover a complete searching area because of the limited searching range and energy of sensor nodes as they are few in number. The author proposes a distributed energy efficient tracking in a hybrid WSN (DEETH) to track a randomly moving target in an unknown searching. Hybrid WSN that is proposed has both static sensor nodes (SSNs) and mobile sensor nodes (MSNs), which are deployed in the searching area. The MSNs move collectively using particle swarm techniques to search a target. The SSNs are deployed for tracking the presence of a target and giving this information to the base station. As per the information given by SSN, MSNs travel to the target and track it. Simulation results prove that proposed technique successfully tracks the target using less number of nodes and also less amount of energy. KEYWORDS energy consumption, particle swarm optimization, RSS-based target tracking, sHybrid wireless sensor network | INTRODUCTIONIn the recent times, wireless sensor network (WSN) has gained momentum and is utilized for border surveillance, mine detection, animal tracking, etc for the purpose of detecting and tracking intruders, observing their behaviors, and controlling their illegal activities. In these applications, a randomly moving tracking target is a common complex problem.A number of techniques are suggested in the literature to provide a solution, but still, there are a lot of challenges like the reliability of networks, communication protocol, usages of heterogeneous sensors in the network, distributed and collaborative data processing, sensor deployment to cover complete searching area, data aggregation, tracking accuracy, and energy consumption. 1 Many authors have proposed their solutions by considering 1 or 2 challenges, but still, there is a need to provide a generic solution for area surveillance. 2,3 In the proposed system, Particle Swarm Optimization (PSO)-based mobile sensor node (MSN) navigation is implemented. 4,5 The objectives of the paper are (1) to simulate randomly moving target searching in an unknown environment, with minimum sensor nodes in hybrid WSN (static sensor node [SSN] and MSN), (2) to efficiently use, PSO technique to achieve group movements of MSNs for target searching, and (3) to compare energy of all approaches.

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Section: Proposed Methodsmentioning

confidence: 99%

Distributed Energy Efficient Tracking in Hybrid wireless sensor network (DEETH)

Nighot

Ghatol

Thakare

2017

Int J Communication

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“…Reactive mobility is exploited to improve the quality of target detection in [6], but the movement of sensors is not considered as the primary optimization objective. In [7] mobile sensors are scheduled to replace failed static sensors in order to guarantee coverage ratio with minimum movement distance. But each sensor concerned in [7] can cover only one target and the maximum moving distance for each mobile sensor is limited.…”

Section: Related Workmentioning

confidence: 99%

“…In [7] mobile sensors are scheduled to replace failed static sensors in order to guarantee coverage ratio with minimum movement distance. But each sensor concerned in [7] can cover only one target and the maximum moving distance for each mobile sensor is limited. In [16], an optimal velocity schedule is proposed to minimize energy consumption in movement when the road condition is uniform.…”

Section: Related Workmentioning

confidence: 99%

Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks

Liao

Wang

Zhang

et al. 2015

IEEE Trans. Parallel Distrib. Syst.

175

114

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Abstract-Coverage of interest points and network connectivity are two main challenging and practically important issues of Wireless Sensor Networks (WSNs). Although many studies have exploited the mobility of sensors to improve the quality of coverage and connectivity, little attention has been paid to the minimization of sensors' movement, which often consumes the majority of the limited energy of sensors and thus shortens the network lifetime significantly. To fill in this gap, this paper addresses the challenges of the Mobile Sensor Deployment (MSD) problem and investigates how to deploy mobile sensors with minimum movement to form a WSN that provides both target coverage and network connectivity. To this end, the MSD problem is decomposed into two sub-problems: the Target COVerage (TCOV) problem and the Network CONnectivity (NCON) problem. We then solve TCOV and NCON one by one and combine their solutions to address the MSD problem. The NP-hardness of TCOV is proved. For a special case of TCOV where targets disperse from each other farther than double of the coverage radius, an exact algorithm based on the Hungarian method is proposed to find the optimal solution. For general cases of TCOV, two heuristic algorithms, i.e., the Basic algorithm based on clique partition and the TV-Greedy algorithm based on Voronoi partition of the deployment region, are proposed to reduce the total movement distance of sensors. For NCON, an efficient solution based on the Steiner minimum tree with constrained edge length is proposed. The combination of the solutions to TCOV and NCON, as demonstrated by extensive simulation experiments, offers a promising solution to the original MSD problem that balances the load of different sensors and prolongs the network lifetime consequently.

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“…(1) there are errors existing in topology duration statistics caused by limited simulating duration; (2) there is an approximate calculation in the link duration fitting function.…”

Section: Topology Durationmentioning

confidence: 99%

“…Each must forward traffic unrelated to its own use and therefore be a router. The primary challenge in building a wireless mobile multihop communication network is equipping each device to continuously maintain the information required to properly route traffic, which is quite difficult since the topology caused by nodes movement keeps changing [1,2]. Relevant studies indicate that the overall performance of wireless mobile multihop communication network is closely related to the adaptability of the network protocol to the dynamic property.…”

Section: Introductionmentioning

confidence: 99%

Topology Property Based on Network Tomography for Wireless Mobile Multihop Communication Network

Qin

Ding

2014

International Journal of Distributed Sensor Networks

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The random movement of nodes makes the dynamic topology structure be one of the most important characteristics in wireless multihop communication network, which makes the description and quantization of the dynamic property the very foundation of the design, simulation, and measurement for this kind of network. The distributions of the link duration and the topology duration will be derived and verified by simulations. Then, the topology flapping sensing method has been put forward based on TTL. Finally, the probability model of the topology stability in the measurement time has been established and calculated based on network tomography for wireless mobile multihop communication network in this paper. Simulating results verify the correctness and efficiency of the approach, which will provide the technique basis of research on the dynamic property and end-to-end measurement for wireless mobile multihop communication network.

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Optimal Mobile Sensor Scheduling for a Guaranteed Coverage Ratio in Hybrid Wireless Sensor Networks

Cited by 11 publications

References 26 publications

Distributed Energy Efficient Tracking in Hybrid wireless sensor network (DEETH)

Distributed Energy Efficient Tracking in Hybrid wireless sensor network (DEETH)

Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks

Topology Property Based on Network Tomography for Wireless Mobile Multihop Communication Network

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