大规模无线传感器网络中高效按需充电规划

随着无线充电技术的日趋成熟,特别是磁共振无线充电技术的发展,利用移动充电车和无线充电技术给无线传感器补充能量,以保证无线传感器网络持续运转,成为新的研究热点。为此,主要介绍在大规模的无线传感器网络中,如何调度多个充电车给网络中的待充电传感器补充能量。为了均衡多个充电车的充电任务,缩小整个充电任务的完成时间,提出了充电总耗时最短问题,希望能为多个充电车找到各自的充电路径,使得多个充电车中耗时最长的任务完成时间最短。因为充电总耗时最短问题是一个NP难问题,难以在多项式时间内找到最优解,所以针对该问题提出了一个近似比为5的近似算法。最后用模拟实验证明了算法的性能,实验表明该算法的实际近似比不足2。

Efficient on-demand charging scheduling in large scale wireless sensor networks

With the increasing maturity of wireless charging technology, especially the development of magnetic resonance wireless charging technology, the employment of mobile charging vehicles and wireless charging technology to replenish sensors'' energy to ensure the continuous operation of wireless sensor networks has become a new research hotspot. This paper focused on how to schedule multiple charging vehicles to replenish energy to the sensors in a large-scale wireless sensor network. In order to balance the charging tasks of multiple charging vehicles and reduce the completion time of the whole charging task, the paper proposed the charging task completion time minimization problem, hoping to find K closed charging circles for K charging vehicles, so that the longest completion time among these K vehicles was the shortest. Since the charging task completion time minimization problem was an NP-hard problem and it was difficult to find an optimal solution in polynomial time, this paper proposed an approximation algorithm with a ratio of 5 for this problem. Finally, it demonstrated the performance of the algorithm by simulation experiments, and the experiments show that the actual approximation ratio of the proposed algorithm is less than 2.