A Newborn Particle Swarm Optimization Algorithm for Charging-Scheduling Algorithm in Industrial Rechargeable Sensor Networks

The Industrial Wireless Rechargeable Sensor Network (IWRSN) is a sensor network used in industrial environments. In order to ensure a certain intensity of industrial monitoring and real-time industrial control, the network is equipped with mobile charger to supplement the energy for sensors according to the charging schedule. Because of the complexity of industrial environment, the monitoring area is firstly divided into grids and established a set of paths that can be driven by mobile chargers. On this basis, a newborn particle swarm optimization (NPSO) charging scheduling algorithm is proposed for the constraint of node working time window. The NPSO algorithm borrows the idea of fireworks algorithm to introduce newborn particles into the population, and improves the convergence speed of the algorithm, then applies it to the charging scheduling process. The NPSO charging algorithm firstly plans the initial scheduling path for the node that needs to be priority charging. The remaining nodes to be charged are then designed to search for the location of the initial path near their position and update the time window of the subsequent charging node. The simulation results show that the proposed newborn particle swarm optimization charging scheduling algorithm has superiority in energy utilization and node mortality compared with the existing charging scheduling algorithm.