Research on Maximum flow Algorithm in Rechargeable Wireless Sensor Networks

LI Tian-xu; XIAO Shuo

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Research on Maximum flow Algorithm in Rechargeable Wireless Sensor Networks

更新时间：2026-09-04

- Research on Maximum flow Algorithm in Rechargeable Wireless Sensor Networks
- Vol. 35, Issue 10, Pages: 116-120(2018)
- 作者机构：
  
  中国矿业大学计算机科学与技术学院,江苏,徐州,221116
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
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李天旭, 肖硕. 可充电无线传感器网络中的最大流算法研究[J]. 微电子学与计算机, 2018, 35(10): 116-120, 126.

LI Tian-xu, XIAO Shuo. Research on Maximum flow Algorithm in Rechargeable Wireless Sensor Networks[J]. 2018, 35(10): 116-120.
李天旭, 肖硕. 可充电无线传感器网络中的最大流算法研究[J]. 微电子学与计算机, 2018, 35(10): 116-120, 126. DOI：

LI Tian-xu, XIAO Shuo. Research on Maximum flow Algorithm in Rechargeable Wireless Sensor Networks[J]. 2018, 35(10): 116-120. DOI：

摘要

通过在传感器网络中一些节点附近部署静态辅助充电器(ACs)的方法

能提升网络中从source节点流向sink节点的最大流量.为此

构建了该问题的混合整数线性规划模型(MILP)

并证明该问题为NP-hard问题

提出首先使用BottleNeck算法为遗传算法生成初始种群

该算法以路径为单位

采用能量最低的节点优先的原则部署ACs

然后使用改进的自适应的遗传算法(IAGA)模拟自然进化过程

搜索部署ACs的最优位置

使到达sink节点的流量达到最大.仿真实验结果表明

与其他的几种布属ACs的方法相比

IAGA可以有效提高到达sink节点的最大流量.

Abstract

A method of deploying static auxiliary chargers (ACs) next to somesensor nodes is used to improve the maximum flow from sources to sinks in the network. So

the research formulates a mixed integer linear program (MILP) for the problem and proves that the problem is NP-hard. Firstly

it proposes to use BottleNeck algorithm whichuses path-by-unit and deploys ACs using the lowest energy node-first principleto generate initial population for genetic algorithm. Then the Improved Adaptive Genetic Algorithm (IAGA) is used to simulate the natural evolutionary process and search for the optimal location for deployment of ACs to maximize the flow rate to sinks. The simulation results show that IAGA can effectively increase the maximum flow arriving at the sinks compared with some other algorithms of distributing ACs.

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Keywords

references

Rappaport T S. Wireless Communications: Principles and Practice[M]. Prentice HallPTR, 1996.

Xiao Y, Chen H, Li F H. Handbook on Sensor Networks[M]. World Scientific, 2010.

Heinzelman W R, Chandrakasan A, Balakrishnan H. Energy-Efficient Communication Protocol for Wireless Microsensor Networks[C]// Hawaii International Conference on System Sciences. IEEE Computer Society, 2000: 4-7.

Zhu C, Liu K, Yu C, et al. Simulation and experimental analysis on wireless energy transfer based on magnetic resonances[C]// Vehicle Power and Propulsion Conference. IEEE, 2008: 1-4.

Kurs A, Karalis A, Moffatt R, et al. Wireless Power Transfer via Strongly Coupled Magnetic Resonances[J]. Science, 2007, 317, 83-86. DOI: 83

Goldberg D E. Genetic Algorithm in Search, Optimization, and Machine Learning[J].1989, xiii(7): 2104-2116.

He T, Chin K W, Soh S. On using Wireless Power Transfer to increase the max flow of Rechargeable Wireless Sensor Networks[C]// IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. IEEE, 2015: 1-6.

Ahuja R K, Magnanti T L, Orlin J B. Network flows: theory, algorithms, and applications[J]. Journal of the Operational Research Society, 1993, 45(11):791-796. DOI: 791

Srinivas M, Patnaik L M. Adaptive probabilities of crossover and mutation in genetic algorithms[J]. IEEE Transactions on Systems Man % Cybernetics, 2002, 24(4):656-667. DOI: 656

Ford L R J, Fulkerson D R. A Simple Algorithm for Finding Maximal Network Flows and an Application to the Hitchcock Problem[J]. Canadian Journal of Mathematics, 1955, 9:210--218. DOI: 210

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