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Collaborative Charging Scheduling in wireless Charging sensor networks

Computers, Materials & Continua 2024年第4期79卷 1613-1630页

作者： Qiuyang Wang Zhen Xu Lei Yang School of Electrical and Electronic Engineering Wuhan Polytechnic UniversityWuhan430048China

wireless sensor networks (WSNs) have the trouble of limited battery power, and wireless charging provides apromising solution to this problem, which is not easily affected by the external environment. In this paper, we studythe recharging of sensors in wireless rechargeable sensor networks (WRSNs) by scheduling two mobile chargers(MCs) to collaboratively charge sensors. We first formulate a novel sensor charging scheduling problem with theobjective of maximizing the number of surviving sensors, and further propose a collaborative charging schedulingalgorithm(CCSA) for WRSNs. In the scheme, the sensors are divided into important sensors and ordinary *** can adaptively collaboratively charge the sensors based on the energy limit ofMCs and the energy demandof sensors. Finally, we conducted comparative simulations. The simulation results show that the proposed algorithmcan effectively reduce the death rate of the sensor. The proposed algorithm provides a solution to the uncertaintyof node charging tasks and the collaborative challenges posed by multiple MCs in practical scenarios.

关键词： wireless rechargeable sensor network mobile charger collaborative charging adaptive charging

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Mobile energy replenishment scheduling based on quantum-behavior particle swarm optimization

Mobile energy replenishment scheduling based on quantum-beha...

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第三十九届中国控制会议

作者： Chengpeng Jiang Fen Liu Jinglin Li Peng LV Wendong Xiao School of Automation and Electrical Engineering University of Science and Technology Beijing Engineering Research Center of Industrial Spectrum Imaging School of Computer and Communication Engineering University of Science and Technology

wireless rechargeable sensor network is a new type of sensor network which has been widely concerned recently. It has the function of charging nodes in network. We use the mobile energy replenishment device to actively move to nodes in the sensor network for charging. Research shows that different charging circuit order will get different charging performance. Therefore, we explore the design of scheduling scheme to achieve better charging performance. In this paper, three new concepts are proposed respectively: the start moment of charging, the energy exhaustion moment and the state of charging to evaluate the scheduling. Based on the above, we define a quadratic performance index as the evaluation of charging performance in sensor network called charging cost of network, the smaller the index is, the better charging performance of the network will be. Through theoretical analysis, firstly, we prove the problem in this paper is NP-complete. Then, considering the charging efficiency of each node to be charged, combined with the quantum behavior particle swarm optimization（QPSO） algorithm, we propose an optimal scheduling scheme for mobile energy replenishment device. Finally, some simulations and theoretical analyses can verify the correctness and effectiveness of the scheme which we proposed.

关键词： wireless rechargeable sensor network mobile energy replenishment quantum behavior particle swarm optimization optimal scheduling

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