Spatiotemporal charging scheduling in wireless rechargeable sensor networks

被引:41
|
作者
Zhao, Chuanxin [1 ]
Zhang, Hengjing [2 ]
Chen, Fulong [1 ]
Chen, Siguang [3 ]
Wu, Changzhi [4 ]
Wang, Taochun [1 ]
机构
[1] Anhui Normal Univ, Sch Comp & Informat, Wuhu 241003, Peoples R China
[2] Univ Sci & Technol China, Sch Comp Sci, Suzhou 215123, Peoples R China
[3] Nanjing Univ Post & Telecommun, Sch Internet Things, Nanjing 210003, Peoples R China
[4] Guangzhou Univ, Sch Management, Guanghzou 510006, Peoples R China
基金
中国国家自然科学基金;
关键词
Wireless sensor network; Wireless charging; Joint optimization; Evolution teaching learning based optimization; Hybrid task; LIFETIME; NODES;
D O I
10.1016/j.comcom.2020.01.037
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wireless sensor networks have a wide range of applications. However, the battery-constrained energy limits the scope of network applications and timeliness. In this paper, we study how to schedule charging and allocate charging time simultaneously for a wireless sensor network for the purpose of prolonging network lifetime and improve charging efficiency. To this end, a mixed integer optimization model for simultaneous charging scheduling and charging time allocation is established through the maximization of the charging efficiency. Then, an offline algorithm is developed to solve the problem. Further, an online charging node insertion algorithm is developed for real-time service. The simulation results show that the proposed algorithm can achieve near 100% charging success rate under periodic and hybrid services, which is significantly superior to the results obtained by the compared algorithms.
引用
收藏
页码:155 / 170
页数:16
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