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计算机工程

• 移动互联与通信技术 • 上一篇    下一篇

基于蚁群优化算法的ReInForM动态路由

彭云建,黄璐   

  1. (华南理工大学 自动化科学与工程学院,广州 510640)
  • 收稿日期:2016-07-05 出版日期:2017-08-15 发布日期:2017-08-15
  • 作者简介:彭云建(1974—),男,副教授,主研方向为光伏发电系统数据采集;黄璐,硕士研究生。
  • 基金资助:
    国家自然科学基金“多路并网光伏发电系统荷-网-源随机网络建模与自主协调监控方法研究”(61573154,60904032);广东省科技计划项目“多路并网光伏发电系统电能量智能监控技术”(2015A010106003)。

ReInForM Dynamic Routing Based on Ant Colony Optimization Algorithm

PENG Yunjian,HUANG Lu   

  1. (School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,China)
  • Received:2016-07-05 Online:2017-08-15 Published:2017-08-15

摘要: 无线传感器网络中ReInForM多路径协议能保证网络可靠性,但未考虑节点能量动态变化和通信路径工况,随机选取下一跳转发节点的方式使得部分节点因被反复使用而快速失效,缩短了网络生命周期。针对该问题,在蚁群优化算法的基础上,结合蚁群信息素浓度和节点剩余能量等因素,提出一种ReInForM协议多目标优化条件下的动态路由选择算法,将能耗和剩余能量作为多路径选择指标,共同决定下一跳最优节点。仿真结果表明,与原有ReInForM路由算法相比,该算法能够在保证数据传输可靠率的同时,更有效地均衡节点能耗。

关键词: 无线传感器网络, ReInForM路由算法, 蚁群优化算法, 能量均衡, 可靠性, 生命周期

Abstract: ReInForM routing protocol in Wireless Sensor Network(WSN) only guarantees network reliability without considering the dynamic changes of node energy and communication path conditions.The way of selecting the next hop forwarding node randomly makes some nodes fail quickly because of repeated use,and further shortens the network life cycle.To solve the above problems,this paper introduces Ant Colony Optimization(ACO) algorithm and combines ant pheromone concentration and node residual energy to construct a ReInForM dynamic routing selection algorithm under the condition of multi-object optimization.It takes the energy consumption and residual energy as the path selection indicators to determine the optimal next hop.Simulation results show that,compared with the original ReInForM routing algorithm,the proposed algorithm can effectively balance the node energy consumption while ensuring the reliability of data transmission.

Key words: Wireless Sensor Network(WSN), ReInForM routing algorithm, Ant Colony Optimization(ACO) algorithm, energy balance, reliability, life cycle

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