Joint on-demand data gathering and recharging by multiple mobile vehicles in delay sensitive WRSN using variable length GA

Numerous state-of-the-art works on joint data gathering and charging (DGAC) believe that the mobile vehicle (MV) has sufficient energy to charge the sensors and collect data from them by travelling across the path. The existing works also considered that the sensors always get full charge from MV which produces negligible dead period and minimum data gathering delay in Wireless Rechargeable Sensor Network (WRSN). However, the aforementioned considerations are not always practical in large-scale WRSN. In this article, we introduce an efficient on-demand partial DGAC scheme using battery limited multiple MV s. The proposed scheme executes the joint DGAC process such that the total dead periods of the sensors and the overall data gathering delay is reduced. We use multi objective-based genetic algorithm (GA) to optimize the entire DGAC process. The simulation is performed to demonstrate the usefulness and competitiveness of the proposed scheme. We also verify the statistical significance of the simulation results using ANalysis Of VAriance (ANOVA). The compar-ative analysis reveals that the proposed work improves the DGAC efficiency by reducing the dead period of sensors, data gathering delay, and energy consumption of MV s in comparison with the existing works.