无人机辅助的无线可充电传感网充电路径规划方案

UAV-assisted Charging Path Planning of Wireless Rechargeable Sensor Networks

针对传统无线可充电传感网(WRSNs)存在传感器节点较为分散导致的充电效率低问题,提出了一种基于对WRSN进行分簇的无人机(UAV)充电路径优化方案(Optimized Charging Path Scheme, OCPS).方案首先将目标区域根据聚类算法划分为不大于充电器最大可覆盖范围的子区域并称其为簇;然后确定各簇区域锚点以及优先级并对充电最优路径进行选择;最后借助无人机给所有簇内传感器节点充能并返回充电中心(Charge Center, CC).仿真实验验证了方案的可行性,实验结果与AEC、MUC方案相比,OCPS方案的充电效率分别提高了约19.5%、27.9%,平均饿死节点数分别降低0.3、1.2个.与CRP、HCCA方案相比,OCPS的飞行长度与充电时长都有明显缩短.

Aiming at the low charging efficiency of traditional wireless rechargeable sensor networks(WRSNs)caused by the relatively scattered sensor nodes, a UAVcharging path optimization scheme(Optimized Charging Path Scheme, OCPS)based on clustering of WRSNsis proposed. The scheme first divides the target area into sub-areas not larger than the maximum coverage area of the charger according to the clustering algorithm and calls them clusters;then determines the anchor points and priorities of each cluster area and selects the optimal charging path;finally, with the help of UAV charges all the nodes in the cluster and returns to the Charge Center(CC). The simulation experiment verified the feasibility of the scheme. Compared with the AEC and MUC schemes, the experimental results showed that the charging efficiency of the OCPS scheme was increased by about 19.5% and 27.9%,respectively, and the average number of starved nodes was reduced by 0.3 and 1.2 respectively. Compared with CRP and HCCA schemes, the flight length and charging time of OCPS are significantly shortened.