Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Abstract

Summary Prolonging network lifetime is a fundamental requirement in wireless sensor network (WSN). Existing charging scheduling algorithms suffer from high node redundancy and energy consumption issues. In this paper, we study WSN charging problem from the perspectives of energy conservation combined with energy replenishment scheduling. Firstly, we detect the redundant nodes whose energy is wasted in the network functionality and develop a K‐covering redundant nodes sleeping scheduling algorithm (KRSS) for reducing energy. Secondly, we employed multiple wireless charging vehicles (WCVs) for energy replenishment and optimize the charging scheduling algorithm to prevent any exhaustion of nodes, and we proposed a distance and energy–oriented charging scheduling algorithm (DECS) with multiple WCVs. Simulation experiments are conducted to show the advantages of the proposed KRSS+DECS, confirming that our scheme is capable of removing redundant nodes, lowering node failures, and prolonging network lifetime.

On Increasing the Energy Efficiency of Wireless Rechargeable Sensor Networks for Cyber-Physical Systems

“…In a bid to optimize the charging scheduling algorithm of a WRSN, a K-covering redundant nodes' inactive scheduling algorithm was proposed by utilizing numerous WCVs to replenish energies so as to prevent exhaustion from nodes in the network [43]. A WRSN optimizing scheduling problem was also studied based on the condition of random events.…”

A Novel Epidemic Model for Wireless Rechargeable Sensor Network Security

“…Owing to electricity consumption, sensor nodes in both S and I drop to low-energy at rate . Meanwhile, when considering rechargeable battery equipped in sensor nodes and charging sensor nodes by multiple wireless charging vehicles [ 41 ], low-energy sensor nodes rise back to their previous states, since their batteries are full of electricity again. Detailedly, in order to simplify the model, assuming that the charging rate C is a constant.…”

Space‐correlation‐based joint data transmission and on‐demand charging for rechargeable wireless sensor networks

“…In fact, in addition to the spatial correlation, the data collected by the same node at different times is also correlated (called time correlation). The time correlation means that the data acquisition frequency can be reduced [15][16][17], further reducing the energy consumption of the node. However, too low acquisition frequency may result in the inability to detect the transient events.…”

“…Wang et al. also investigated the energy waste of redundant nodes and developed a K ‐covering redundant node sleeping scheduling algorithm to reduce energy [16].…”