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

• Main Authors: Jiang, Chengpeng, Liu, Fen, Li, Jinglin, LV, Peng, Xiao, Wendong
• Format: Conference Proceeding
• Language: English
• Subjects: Energy consumption; Energy storage; mobile energy replenishment; Monitoring; Optimal scheduling; quantum behavior particle swarm optimization; Scheduling; Temperature sensors; wireless rechargeable sensor network; Wireless sensor networks
• ISSN: 2161-2927
• DOI: 10.23919/CCC50068.2020.9188458

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.