Efficient utilization of energy of the network is one of the major issues faced by wireless sensor network, when sensors are placed in a hostile environment. One of the methods to solve this problem is to activate onl...
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ISBN:
(纸本)9781509063024
Efficient utilization of energy of the network is one of the major issues faced by wireless sensor network, when sensors are placed in a hostile environment. One of the methods to solve this problem is to activate only a few sensors which satisfy the coverage constraints. This can be done by partitioning a set of all sensors into many subsets or sensor covers such that each sensor cover satisfies the coverage constraints and activating them subsequently which leads to increase the network lifetime. A memetic algorithm is proposed in this paper for the Q coverageproblem where each target can be covered by one or more sensors. The cardinal objective of the proposed algorithm is to maximize the lifespan of the network while satisfying the coverage constraints. The proposed algorithm avoids redundancy and utilizes the available resources to maximize the network lifetime. Simulation results show that our proposed algorithm performs better than the existing algorithms.
coverage is a broad research area in wireless sensor networks. In order to maximize network lifetime for targetcoverage, we study the target coverage problem with multiple sensing ranges, which has been proved NP-com...
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ISBN:
(纸本)9781424481804
coverage is a broad research area in wireless sensor networks. In order to maximize network lifetime for targetcoverage, we study the target coverage problem with multiple sensing ranges, which has been proved NP-complete. For CGH algorithm [13] that introduces many redundant sensors in each round, we propose an Energy-efficient Centralized Greedy and Heuristic algorithm (ECGH), which introduces a concept of "remote target", and adopts a scheme, where sensors that can cover the "remote target" are selected with a high priority. ECGH algorithm depends on global information, so we propose an Energy-efficient Distributed and Localized Greedy Heuristic algorithm (EDLGH). Different from DLGH algorithm [13], EDLGH algorithm schedules sensors in a more energy-efficient way. Besides, an efficient schema for eliminating redundant sensors is also proposed in the EDLGH algorithm. Finally, we study the performance of ECGH and EDLGH by comparing them with existing CGH and DLGH algorithms. Simulation results show that network lifetime of ECGH and EDLGH outperform 7.9 %-10.2 % and almost 100 % than those of CGH and DLGH, respectively.
Achieving maximum coverage of targets in a sensing network while minimizing the usage of directional sensors presents a formidable challenge. The rising popularity of pivoting directional sensors, capable of scanning ...
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The primary challenge of a remotely located wireless sensor network in an unmanned application is to maximize the network lifetime, and it is achieved by effective usage of available resources. The efficient way to us...
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The primary challenge of a remotely located wireless sensor network in an unmanned application is to maximize the network lifetime, and it is achieved by effective usage of available resources. The efficient way to use the available resources in wireless sensor network is to partition the deployed sets of all sensors into disjoint subsets or sensor covers such that each sensor cover can monitor the entire target at any time. Furthermore, this way of maximizing sensor lifetime by activating sensor cover one after another is found to be effective without exploiting the resource availability. In this paper, the cuckoo search algorithm is proposed to identify the maximum number of sensor covers. It is observed that the proposed algorithm outperforms than existing algorithms by eliminating redundant sensors and supplementing with a sensor when it is required. The simulation results of various problem instances show the superiority of proposed algorithm in terms of network lifetime, and it is validated by comparison with other few existing algorithms. (C) 2020 Elsevier Ltd. All rights reserved.
In order to reduce the algorithm complexity of the target coverage problem which is a NP-complete problem,we design three approaches to shorten the network *** firstly delete redundant sensor nodes,secondly remove the...
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In order to reduce the algorithm complexity of the target coverage problem which is a NP-complete problem,we design three approaches to shorten the network *** firstly delete redundant sensor nodes,secondly remove the redundant targets,and thirdly divide the target-coverage graph into independent sub-graphs,and present the construct independent sub graph algorithm(CISGA) to divide target-coverage *** results show that CISGA could reduce 30% of network scale and greatly reduce the algorithm complexity of target coverage problem.
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