一种新的交叉口车辆聚类算法

Yu Zhou, Xia Wu, Ping Wang
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引用次数: 2

摘要

由于提高了路由协议的稳定性和可扩展性,集群技术逐渐成为车载自组织网络(VANET)的重要技术之一。针对现有算法在交叉场景下簇头(CH)丢包率大、稳定性低的问题,提出了一种新的簇成员(CM)数据更新机制。它是根据CM的路段和CH的路段动态更新,而不是周期性更新。此外,为了选择更有效的CH,我们利用基站(BS)收集其周围路段的车辆信息,然后利用车辆之间的相对位置和车辆到基站的相对距离,利用BS进行新的CH选举。最后,提出了一种新的路段队列概念,以提高交叉口场景下集群的稳定性。采用SUMO和omement++进行的仿真结果表明,本文提出的聚类算法可以显著提高交叉场景下的丢包率、开销和聚类稳定性。
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A novel vehicle clustering algorithm in intersection scenario
Clustering technology gradually becomes one of the most important technologies in vehicular ad hoc network (VANET) due to improve the stability and scalability of routing protocols. To overcome the large packet loss rate and low stability of cluster head (CH) in the existing algorithms in intersection scenario, in this paper, we propose a new cluster member (CM) data updating mechanism. It is updating dynamically according to the road section of CM and the road section of CH, instead of updating periodically. Additionally, in order to select a more valid CH, we utilize the base station (BS) to collect the information of vehicles on the road sections around it, and then use the BS to carry out a new CH election by using the relative position between vehicles and the relative distance from the vehicle to the BS. Finally, a new concept of the road section queue is proposed to improve the stability of cluster in intersection scenario. The simulation results by employing SUMO and OMENT++ show that the proposed clustering algorithm can improve the packet loss rate, overhead and cluster stability significantly in intersection scenario.
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