无线可充电传感器网络下的高维多目标动态充电规划

Many-objective Dynamic Charging Scheme in Wireless Rechargeable Sensor Networks

随着无线充电传感器网络(Wireless Rechargeable Sensor Networks,WRSNs)的出现,针对延长无线传感器网络(Wireless Sensor Networks,WSNs)的寿命问题,大量的研究者们提出了多种充电方案.然而大多数充电方案都属于离线的,没有考虑充电路径规划会随着新需充电节点的加入而发生动态变化的多时间窗问题.因此,针对上述问题,本文提出了高维多目标动态充电路径方案模型.通过最小化路径距离、死亡节点数量、通信延迟以及最大化无线充电车(Wireless Charging Vehicle,WCV)剩余能量,以减少死节点数量,延长WRSNs的生命周期.同时为求解该动态模型以及适应路径编码方式和响应环境变化,通过引入改进的进化策略和环境响应机制到强帕累托进化算法2(The Strength Pareto Evolutionary Algorithm 2,SPEA2)中,提出了改进的SPEA2.仿真实验结果表明,该动态模型和改进算法能够有效地延长WRSNs的生命周期.

With the emergence of wireless rechargeable sensor network(WRSN),the various charging schemes are proposed for prolonging the lifetime of the wireless sensor networks(WSNs).But most of charging schemes are off-online and lack of consideration for the multiple time windows problems that the charging path planning will change dynamically with the addition of new charging nodes.Therefore,in this paper,we propose the many-objective dynamic charging path scheme model for reducing the number of dead nodes and prolonging the life cycle of WRSNs.These four objectives in dynamic model are optimized simultaneously,including respectively the path distance,the number of dead nodes,the residual energy of the wireless charging vehicle(WCV)and the delay time of communication.In order to solve the dynamic model,the improved the strength pareto evolutionary algorithm 2(SPEA2)is proposed.The improved evolutionary strategy and the environmental respond mechanism are introduced into the SPEA2 in order to adapt the coding mode of path and respond to changes in the environment when new nodes are added the charging programming.The simulation comparison results show that the dynamic model and algorithm are reasonable and the life cycle of WSNs can be effectively extended.