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移动无线可充电传感器网络中的充电路径优化

牛权龙 贾日恒 李明禄

物联网学报2023,Vol.7Issue(4):110-122,13.
物联网学报2023,Vol.7Issue(4):110-122,13.DOI:10.11959/j.issn.2096-3750.2023.00364

移动无线可充电传感器网络中的充电路径优化

Charging path optimization in mobile wireless rechargeable sensor networks

牛权龙 1贾日恒 1李明禄1

作者信息

  • 1. 浙江师范大学计算机科学与技术学院,浙江 金华 321004
  • 折叠

摘要

Abstract

The wireless power transfer technique is promising in solving the energy bottleneck of sensor nodes in wire-less sensor networks,which can thus prolong the network lifetime or even maintain sustainable network operations.Most existing works focused on optimizing the static chargers'deployment or mobile chargers'charging path for static sensor nodes with fixed sensor node positions,ignoring the scenario with mobile sensor nodes.Thus,design and optimize the charging path of a mobile charger was studied for dynamic wireless sensor networks with mobile sensor nodes,to maxi-mize the charging utility within a finite time horizon,that is,the charger can encounter as more sensor nodes as possible in a limited time and charge them.Notice that the mobile charger may stop to simultaneously charge multiple nodes within its charging range during its charging tour.The proposed charging path optimization problem was proven to be an APX-hard problem.Then,based on the constructed directed acyclic graph using discretization method,a layer-wise pruning algorithm based on the backtracking method was proposed.The proposed algorithm took the solution generated by the greedy algorithm as the benchmark and searched the optimal charging path under a fixed time division by lay-er-wise pruning.Simulation results show that the proposed algorithm can effectively improve the charging utility.

关键词

移动无线网络/移动充电器调度/分层剪枝算法

Key words

mobile wireless network/mobile charger scheduling/layer-wise pruning algorithm

分类

信息技术与安全科学

引用本文复制引用

牛权龙,贾日恒,李明禄..移动无线可充电传感器网络中的充电路径优化[J].物联网学报,2023,7(4):110-122,13.

基金项目

国家自然科学基金资助项目(No.62272417)The National Natural Science Foundation of China(No.62272417) (No.62272417)

物联网学报

OACSTPCD

2096-3750

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