Electronic Science and Technology ›› 2022, Vol. 35 ›› Issue (6): 13-20.doi: 10.16180/j.cnki.issn1007-7820.2022.06.003

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Maximizing the Rest Time of Mobile Charger in Rechargeable Probabilistic Sensor Networks

RAN Xianyuan,WANG Ran   

  1. College of Computer Science and Technology,Hangzhou Dianzi University,Hangzhou 310018,China
  • Received:2021-03-05 Online:2022-06-15 Published:2022-06-20
  • Supported by:
    Key R&D Program of Zhejiang(2020C01067)


Under the condition of ensuring the permanent coverage of the target point in the wireless rechargeable sensor network, based on the probabilistic monitoring model and the multi-node charging model, the problem of maximizing the rest time ratio of the mobile charger in the rechargeable sensor network is studied. By relaxing the restriction on the immortality of sensors, the charging selection algorithm based on unit sub-cluster and entire-based re-clustering heuristic algorithm are proposed. The redundant sensors around the target point are constructed into target clusters and sub-clusters are divided according to the greedy idea. By adjusting the distance requirements within the sub-clusters and re-clustering the global request nodes, the anchor points are selected for charging, thereby reducing the hybrid gain of the sub-clusters and reducing the number of anchor points. Simulation experiments show that compared with the single-node charging model, the new algorithm improves the rest time of the mobile charger by 10%~15%.

Key words: wireless rechargeable sensor network, probabilistic monitoring model, multi-nodes charging model, mobile charger, charging schedule, the rest time of mobile charger, anchor point, path planning

CLC Number: 

  • TP393