An Online Charging Scheme for Wireless Rechargeable Sensor Networks Based on a Radical Basis Function

Sensors

Jian-Shuang Bai¹  Jia Yang¹  Qiang Xu² 

[1] Chongqing Energy Internet Engineering Technology Research Center, Chongqing University of Technology, No. 69 Hongguang Avenue, Chongqing 400054, China;College of Computer Science and Technology, Chongqing Technology and Business University, No. 19 Xuefu Avenue, Chongqing 400067, China;

关键词: wireless rechargeable sensor network;    online charging schemes;    rbf neural network;    the dynamic energy consumption rate;    energy hole rate;   

DOI  :  10.3390/s20010205

来源: DOAJ

【 摘 要 】

The node energy consumption rate is not dynamically estimated in the online charging schemes of most wireless rechargeable sensor networks, and the charging response of the charging-needed node is fairly poor, which results in nodes easily generating energy holes. Aiming at this problem, an energy hole avoidance online charging scheme (EHAOCS) based on a radical basis function (RBF) neural network, named RBF-EHAOCS, is proposed. The scheme uses the RBF neural network to predict the dynamic energy consumption rate during the charging process, estimates the optimal threshold value of the node charging request on this basis, and then determines the next charging node per the selected conditions: the minimum energy hole rate and the shortest charging latency time. The simulation results show that the proposed method has a lower node energy hole rate and smaller charging node charging latency than two other existing online charging schemes.

【 授权许可】

Unknown