吉首大学学报(自然科学版) ›› 2026, Vol. 47 ›› Issue (4): 19-28.DOI: 10.13438/j.cnki.jdzk.2026.04.004

• 计算机 • 上一篇    下一篇

基于多维度指标遗传算法的按需距离矢量路由协议

麻浩崴,唐志军,董珊珊   

  1. (湖南科技大学信息与电气工程学院,湖南 湘潭 411201)
  • 出版日期:2026-07-25 发布日期:2026-08-06
  • 作者简介:麻浩崴(2000—),男,湖南花垣人,湖南科技大学信息与电气工程学院硕士研究生,主要从事移动自组织网络研究
  • 基金资助:
    国家自然科学基金-湖南科技大学转移项目(K1A169)

AODV Routing Protocol Based on Multi-Dimensional Metrics and Genetic Algorithm

MA Haowei,TANG Zhijun,DONG Shanshan   

  1. (School of Information and Electrical Engineering,Hunan University of Science and Technology,Xiangtan 411201,Hunan China)
  • Online:2026-07-25 Published:2026-08-06

摘要:按需距离矢量路由(AODV)协议在移动自组织网(MANET)中仅采用最小跳数作为路由决策,从而导致路径脆弱、网络寿命短等,针对这个问题,提出了一种基于多维度指标遗传算法的按需距离矢量路由(MOGA-AODV)协议.该路由协议摒弃传统单一路由度量方式,构建了一个结合节点能耗、链路拥塞程度和链路稳定性的复合适应度函数,并引入遗传算法进行路径寻优,以实现对路由选择的系统性优化.仿真实验结果表明,与AODV协议和多指标按需距离矢量路由协议相比,MOGA-AODV协议在平均端到端时延、数据包分组交付率和路由控制开销等性能指标上均表现更优,能够有效增强网络稳定性并延长生命周期,适用于动态复杂的MANET应用场景.

关键词: 按需距离矢量路由协议, 移动自组织网络, 遗传算法, 多维度指标

Abstract: Aiming at the problems of fragile paths and short network lifetime caused by the traditional Ad Hoc On-Demand Distance Vector (AODV) routing protocol,which only takes the minimum hop count as the routing decision criterion in Mobile Ad Hoc Network (MANET),this paper proposes an improved AODV Protocol Based on Multi-Dimensional Metric Genetic Algorithm (MOGA-AODV).Different from the conventional single routing metric mode,the proposed protocol constructs a composite fitness function integrating node residual energy,link congestion degree and link failure probability,and adopts the genetic algorithm for path optimization to realize systematic optimization of route selection.Simulation results show that compared with the traditional AODV and AODV-M protocols,MOGA-AODV achieves substantial improvements in average end-to-end delay,packet delivery ratio and routing control overhead.It can effectively enhance network stability and extend network lifetime,and is applicable in dynamic and complex MANET scenarios.

Key words: Ad Hoc On-Demand Distance Vector routing, mobile ad hoc network, genetic algorithm, multi-dimensional metrics

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