首页|Deployment optimization for target perpetual coverage in energy harvesting wireless sensor network

Deployment optimization for target perpetual coverage in energy harvesting wireless sensor network

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Energy limitation of traditional Wireless Sensor Networks(WSNs)greatly confines the network lifetime due to generating and processing massive sensing data with a limited battery.The energy harvesting WSN is a novel network architecture to address the limitation of traditional WSN.However,existing coverage and deployment schemes neglect the environmental correlation of sensor nodes and external energy with respect to physical space.Comprehensively considering the spatial correlation of the environment and the uneven distribution of energy in energy harvesting WSN,we investigate how to deploy a collection of sensor nodes to save the deployment cost while ensuring the target perpetual coverage.The Confident Information Coverage(CIC)model is adopted to formulate the CIC Minimum Deployment Cost Target Perpetual Coverage(CICMTP)pmblem to minimize the deployed sensor nodes.As the CICMTP is NP-hard,we devise two approximation algorithms named Local Greedy Threshold Algorithm based on CIC(LGTA-CIC)and Overall Greedy Search Algorithm based on CIC(OGSA-CIC).The LGTA-CIC has a low time complexity and the OGSA-CIC has a better approximation rate.Extensive simulation results demonstrate that the OGSA-CIC is able to achieve lower deployment cost and the performance of the proposed algorithms outperforms GRNP,TPNP and EENP algorithms.

Energy harvesting WSNDeployment optimizationConfident information coverage(CIC)Target perpetual coverage

Zhenkun Jin、Yixuan Geng、Chenlu Zhu、Yunzhi Xia、Xianjun Deng、Lingzhi Yi、Xianlan Wang

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Wuhan Business University,430056,China

Wuhan Research Institute of Post and Telecommunication,Wuhan,430074,China

Hubei Key Laboratory of Distributed System Security,Hubei Engineering Research Center on Big Data Security,School of Cyber Science and Engineering,Huazhong University of Science and Technology,Wuhan,430074,China

Hubei Chutian Expressway Digital Technology Co.Ltd Wuhan,430074,China

School of Information and Safety Engineering,Zhongnan University of Economics and Law,Wuhan,430073,China

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National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaShenzhen Science and Technology ProgramWuhan Business University Doctoral Fundamental Research FundsArtificial Intelligence and Intelligent Transportation Joint Technical Center of HUST and Hubei Chutian Intelligent Transportati

6187120962272182619012102022CF0112021KB005

2024

10.1016/j.dcan.2023.02.009

数字通信与网络(英文)

数字通信与网络(英文)

ISSN：
年,卷(期)：2024.10(2)
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