A Novel Two-Mode QoS-Aware Mobile Charger Scheduling Method for Achieving Sustainable Wireless Sensor Networks

For developing a sustainable wireless sensor network (WSN), wireless energy charging and mobile data collection are two promising techniques for enhancing energy efficiency and achieving semi-permanent operation time of WSNs. Currently, many energy-aware methods have been developed by adopting these two technologies. However, joint methods that can combine the advantages of both are still lacking. Technically, by reducing the transmission energy consumption of individual nodes while wirelessly charging low power nodes, the joint method can better extend the operating time of the nodes in the system, improving the overall system life. Therefore, we design a two-mode QoS-aware mobile chargers (MCs) scheduling method for implementing both energy charging and data collection tasks simultaneously. The proposed scheme is comprised of two parts: 1) A new clustering algorithm is designed for addressing the trade-off problemregarding the delay and load balancing of sensors, and the network topology construction. 2) Two heuristicMC scheduling algorithms are introduced for facing the different delay requirements of systems, i.e., the single-path scheduling scheme (SPSS) and the multiple-path scheduling scheme (MPSS). The simulation results show that our proposed method outperforms the existing state-of-the-art approaches in the control group regarding the average delay and the charging utility.

Automated summary

This study proposes a QoS-aware mobile chargers scheduling method that can simultaneously achieve energy charging and data collection tasks. The method consists of two parts: a clustering algorithm to address the delay and load balancing issues of sensors, and two heuristic scheduling algorithms for different delay requirements. Simulation results show that the proposed method outperforms existing approaches in terms of average delay and charging utility.