A many-objective optimization charging scheme for wireless rechargeable sensor networks via mobile charging vehicles

In wireless rechargeable sensor networks (WRSNs), the energy can be transferred from the mobile charging vehicles (MCVs) to sensor nodes via the wireless medium, so that providing a new paradigm to prolong the network lifetime. However, the network lifetime of MCV-enabled WRSNs is affected by several factors such as the charging priority of sensor nodes. Moreover, the communication protocols can dynamically affect the energy consumptions of sensor nodes, which should be taken into account. In this paper, we consider a low energy adaptive clustering hierarchy (LEACH)-based WRSNs, and formulate an MCV deployment manyobjective optimization problem (MDMaOP) for replenishing energy to sensor nodes, in which the number of sensor nodes within the charging ranges of the MCVs, motion energy consumptions of the MCVs, remaining energy of the node with the least residual energy and distance between the MCVs and sensor nodes are simultaneously optimized, to prolong the network lifetime. Moreover, the formulated MDMaOP is analyzed and proven as NP-hard. Then, we propose a fast optimization approach and an accurate optimization approach to solve the formulated problem for satisfying the demands of calculation time and accuracy in different scenarios. Simulation results demonstrate that the proposed methods are effective for prolonging the network lifetime and outperform some other comparison algorithms.