Abstract: Wireless Sensor Networks(WSNs) are widely deployed in various applications,including military surveillance,disaster prediction,and hazardous environment exploration.However,the limited lifespan of wireless sensors necessitates frequent battery replacements,leading to high maintenance costs and significant inconvenience.In recent years,with the advent of wireless power transmission technology,wireless rechargeable sensor networks(WRSNs) have been developed to address these issues,providing new avenues for research.Nonetheless,existing studies typically prioritize charging capacities,underestimating the urgency and heterogeneity of sensors in emergency scheduling.Formally,this paper treats the scheduling task as a constrained optimization problem with the aim to maximizing the monitoring utility for heterogeneous sensors,which has been proven to be NP-hard.Therefore,it converts the problem to sub-modular maximization through the discretization of charging time.This naturally leads to develop approximate algorithms based on a greedy strategy,with theoretical backing for the approximation ratio to the optimal value.Extensive experiments demonstrate that the proposed algorithms can significantly enhance monitoring utility,with the highest improvement reaching 279.79% compared to the classical NJNP algorithm.

Key words: Wireless rechargeable sensor network, Mobile charging, Discretization of charging time, Submodular function, Approximation algorithm