车载自组网中一种自适应粒子群算法的研究  

Research on an Adaptive Particle Swarm Optimization Algorithm in VANET

作　　者：周杰英[1] 彭石[1] 刘映淋 许杨鹏 

机构地区：[1]中山大学电子与信息工程学院,广州510006

出　　处：《现代计算机（中旬刊）》2017年第4期26-30,共5页Modern Computer

基　　金：广东省省级科技计划项目(No.2015A010103007)

摘　　要：车载自组网又称VANET,具有车辆节点高速移动、拓扑变化快、通信链路不稳定等特点。传统路由协议不能很好适应动态多变的车载环境,所提出的自适应路由协议方法在相邻网络节点间建立马尔科夫链路信息表RLM,然后利用改进的粒子群路由算法选择数据包传递经过的下一跳节点;实验仿真表明,采用RLM监控机制有效解决VANET网络中传输链路不稳定的问题,减少数据包丢包的发生概率,而使用粒子群路由算法有效降低数据包传输时出错的概率,降低时延,从而提高分组投递率。Characteristics such as high speed, changing network topology and unstable communication link exist in the design of VANET routing protocols. Traditional protocols cannot adapt to the dynamic environment of VANET. Proposes a routing protocol based on Markoff route link model between adjacent nodes and uses a novel particle swarm optimization algorithm to select the optimum node that the packet passes through. Simulation results show that the monitoring mechanism solves the problem of unstable communication link in VANET, re- duces the probability of packet loss. And the improved particle swarm optimization algorithm can effectively reduce the probability of transmission error. The delay is reduced and packet delivery ratio of the network is improved.

关 键 词：VANET 粒子群算法 时延 连通性 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]