车联网中基于D-S理论的GPSR改进算法

Improved GPSR algorithm based on D-S theory in VANET

在传统GPSR协议基础上,面对车联网节点快速移动、拓扑结构变化频繁等特点,提出综合度量节点距离、角度、速度矢量、节点密度的GPSR综合度量算法。针对在现实生活中,节点集之中可能存在的节点恶意行为导致的网络性能下降问题,无线网络波动丢包造成的疑似恶意节点行为,建立一种基于D-S证据理论的信任模型。将该模型应用于GPSR综合度量算法中,度量车联网中的节点,甄别恶意节点。仿真结果表明,该算法可有效检测恶意节点,提高了网络性能。

Based on the traditional GPSR protocol,a GPSR synthesis metric algorithm that measured distances,angles,velocity vectors,and node densities of metrics was presented,in the face of the rapid movement of nodes and frequent changes of topology structure.Aiming at the problem of network performance degradation caused by malicious behaviors of malicious nodes that may exist in node sets in real life,and the behavior of suspected malicious nodes caused by wireless network packet loss,a trust model based on D-S evidence theory was established.This model was applied to the GPSR synthesis metric algorithm to measure the nodes in the vehicular ad hoc networks(VANETs)and the malicious nodes were identified.Experimental results show that the proposed algorithm can effectively detect malicious nodes and improve network performance.