Abstract

In recent years, wireless charging technology has provided an alternative to charging equipment. Wireless charging technology has already proved to be useful in our daily lives in phones, buses, restaurants, etc. Wireless charging technology can also be applied in energy-bounded wireless sensor networks (WSNs), and these are called wireless rechargeable sensor networks (WRSNs). The optimized charging path problem is the most widely discussed issue in employing WRSNs with wireless charging vehicles (WCVs). This problem involves determining the most efficient path for charging sensor nodes. Further, charging-scheduling problems also need to be considered in the optimized charging path problem. In this paper, we proposed a multi-module charging strategy (MMCS) used to prolong the lifetime of the entire WRSN. MMCS can be divided into three stages: the charging topology, charging scheduling, and charging strategy stages, with multiple modules in each stage. The best module combination of MMCS is the distance-based module in the charging topology stage, delay-based module in the charging schedule stage, and the average lifetime module in the charging strategy stage. The best module combination enables prolonging the lifetime efficiently, as it considers not only the priority of urgent nodes but also the travel distance of WCV; the delay-based module of the charging schedule stage considers the delay effect on the follow-up nodes. The experimental results show that the proposed MMCS can improve the lifetime of the entire WRSN and that it substantially outperforms the nearest job next with preemption (NJNP) method in terms of lifetime improvement of the entire WRSN.

Highlights

  • As the maturity of wireless charging technology increased, researchers began using wireless charging for wireless sensor networks (WSNs), resulting in implementations defined as wireless rechargeable sensor networks (WRSNs)

  • Because the features of the WSNs contribute to high node replacement costs, the deployed sensor nodes are not changed after deployment

  • Guo et al [8] studied the issue of combining simultaneous wireless charging with mobile data collection an optimized travel strategy that finds the best location for multi‐charging situations and proved that in WRSNs, with a goal of maximizing the efficiency of the WSN using the wireless charging vehicles (WCVs)

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Summary

Introduction

As the maturity of wireless charging technology increased, researchers began using wireless charging for wireless sensor networks (WSNs), resulting in implementations defined as wireless rechargeable sensor networks (WRSNs). Replacing large numbers of the sensor nodes or replacing nodes in remote areas drives the high replacement costs Some of of these sensor nodes may serve as an ,these thesesensor sensornodes nodesare arelimited limitedbyby battery. These sensor nodes thatasserve as key components will their supply earlier, impacting availability in WSNs by causing a gap in sensing capability or even collapse energy supply earlier, impacting availability in WSNs by causing a gap in sensing capability or even of the WSN These issues cause inaccurate results or unacceptably reduce the precision of collapse of the WSN. Since the sensor nodes are nodes randomly distributed in the ground, WCV the must determine an appropriate travel path to the charge the sensor.

Related
1: Energy Constraints of WCV 1
Problem Definition
Method Description
The Stage of Charging Topology
The Stage of Charging Scheduling
An Example of Multi-Module Charging Strategy
Experimental Results and Analysis
Result of Return on Investment Analysis of Battery
Result of Return
Efficiency of Battery
Extended Lifetime of Wireless Rechargeable Sensor Networks
Distribution of the Rescuedthe
Comprehensive
Effect of Variation of the Amount of Charge
The Analysis of Density
Conclusions
Full Text
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