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A low complexity clustering approach enabling context awareness in sparse VANETs

机译:一种低复杂度的群集方法,可在稀疏VANET中实现上下文感知

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This paper deals with a clustering approach for VANETs operating in sparse highway scenarios. The proposed protocol is able to keep high and stable the network connectivity level to allow data exchange among nodes and, thus, achieving context awareness. The criterion adopted in forming a cluster involves the periodic distributed evaluation of connectivity indicators combining the number of neighbors and their distances, without excessive signaling overhead. In this way, data propagation leverages on vehicles physical movements instead of setting up a communications backbone, which can not properly face a high mobility level. The performance has been analyzed in a practical scenario adopting IEEE 802.11p communications standard. In particular, the election period has been optimized for different coverage ranges, pointing out the suitability of the proposed metrics.
机译:本文讨论了在稀疏高速公路场景中运行的VANET的集群方法。所提出的协议能够保持较高且稳定的网络连接级别,以允许节点之间进行数据交换,从而实现上下文感知。形成集群所采用的标准包括对连通性指标的定期分布式评估,该指标结合了邻居的数量及其距离,而没有过多的信令开销。这样,数据传播将依靠车辆的物理运动,而不是建立无法正确面对高移动性水平的通信主干。在采用IEEE 802.11p通信标准的实际情况下已对性能进行了分析。特别是,已针对不同的覆盖范围优化了选举期,指出了建议指标的适用性。

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