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Open AccessArticle

A Joint Optimization Strategy of Coverage Planning and Energy Scheduling for Wireless Rechargeable Sensor Networks

1
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
2
Electronic and Communication Engineering, Beijing Electronics Science and Technology Institute, Beijing 100070, China
3
School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Processes 2020, 8(10), 1324; https://doi.org/10.3390/pr8101324
Received: 25 September 2020 / Revised: 16 October 2020 / Accepted: 16 October 2020 / Published: 21 October 2020
(This article belongs to the Special Issue Smart Systems and Internet of Things (IoT))
Wireless Sensor Networks (WSNs) have the characteristics of large-scale deployment, flexible networking, and many applications. They are important parts of wireless communication networks. However, due to limited energy supply, the development of WSNs is greatly restricted. Wireless rechargeable sensor networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a two-phase scheme is proposed to improve the energy management efficiency for WRSNs. In the first phase, we designed an annulus virtual force based particle swarm optimization (AVFPSO) algorithm for area coverage. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a queuing game-based energy supply (QGES) algorithm was designed. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy supply, and then extends the lifetime of WSN. View Full-Text
Keywords: wireless rechargeable sensor network; coverage optimization; virtual force; particle swarm optimization; queuing game wireless rechargeable sensor network; coverage optimization; virtual force; particle swarm optimization; queuing game
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MDPI and ACS Style

Gong, C.; Guo, C.; Xu, H.; Zhou, C.; Yuan, X. A Joint Optimization Strategy of Coverage Planning and Energy Scheduling for Wireless Rechargeable Sensor Networks. Processes 2020, 8, 1324. https://doi.org/10.3390/pr8101324

AMA Style

Gong C, Guo C, Xu H, Zhou C, Yuan X. A Joint Optimization Strategy of Coverage Planning and Energy Scheduling for Wireless Rechargeable Sensor Networks. Processes. 2020; 8(10):1324. https://doi.org/10.3390/pr8101324

Chicago/Turabian Style

Gong, Cheng; Guo, Chao; Xu, Haitao; Zhou, Chengcheng; Yuan, Xiaotao. 2020. "A Joint Optimization Strategy of Coverage Planning and Energy Scheduling for Wireless Rechargeable Sensor Networks" Processes 8, no. 10: 1324. https://doi.org/10.3390/pr8101324

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