Collaborative Energy Optimization of Multiple Chargers Based on Node Collaborative Scheduling

IF 1.9 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Distributed Sensor Networks Pub Date : 2023-06-05 DOI:10.1155/2023/5092972

Minghua Wang, Yingcong Zeng, Jiaqing Li, Yan Wang

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引用次数: 0

Abstract

Wireless rechargeable sensor network (WRSN) uses mobile chargers (MCs) to charge sensor nodes wirelessly to solve the energy problems faced by traditional wireless sensor network. In WRSN, mobile charging schemes with multiple MCs supplementing energy are quite common. How to properly plan the MC’s moving path to reduce the charge energy loss and deploy nodes to improve network coverage rate has become a huge research challenge. In this paper, a collaborative energy optimization algorithm (CEOA) is proposed for multiple chargers based on k-mean++ and node collaborative scheduling. The CEOA combines internal energy optimization and external device power supply, effectively prolongs network lifetime, and improves network coverage rate. It uses the k-mean++ to cluster nodes in the network; then, the nodes in the network are scheduled to sleep based on the confident information coverage (CIC) model. Finally, the CEOA uses a main mobile charger to carry multiple auxiliary mobile chargers to charge all the nodes in the cluster. Simulation results show that the proposed algorithm increases the network lifetime by more than 8 times and the coverage rate by about 20%.

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基于节点协同调度的多充电器协同能量优化

无线可充电传感器网络（WRSN）使用移动充电器（MC）对传感器节点进行无线充电，以解决传统无线传感器网络面临的能源问题。在WRSN中，具有多个MC补充能量的移动充电方案非常常见。如何正确规划MC的移动路径以减少电荷能量损失，并部署节点以提高网络覆盖率，已成为一个巨大的研究挑战。本文提出了一种基于k-均值++和节点协同调度的多充电器协同能量优化算法（CEOA）。CEOA结合了内部能源优化和外部设备供电，有效延长了网络寿命，提高了网络覆盖率。它使用k-均值++对网络中的节点进行聚类；然后，基于置信信息覆盖（CIC）模型来调度网络中的节点休眠。最后，CEOA使用一个主移动充电器携带多个辅助移动充电器为集群中的所有节点充电。仿真结果表明，该算法将网络寿命提高了8倍以上，覆盖率提高了20%左右。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Distributed Sensor Networks 工程技术-电信学

CiteScore

6.50

自引率

4.30%

发文量

审稿时长

3.6 months

期刊介绍： International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.