Proactive Caching for Vehicular Ad hoc Networks Using The City Model

Yousef AlNagar, Sameh Hosny, A. El-Sherif
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引用次数: 4

Abstract

Caching at Roadside Units (RSUs) is a promising technique to alleviate the load on network backhaul in Vehicular AdHoc Networks (VANETs). It also allows us to minimize communications latency between RSUs and connected vehicles, which are interested in massive multimedia contents. This work proposes novel proactive caching schemes at RSUs for the city mobility environment. We adopt the Manhattan city model, where streets are arranged in an organized manner and movable nodes are allowed to traverse along the grid of horizontal and vertical streets. Exploiting the information about vehicles demand and mobility patterns increases the caching capability and enables us to proactively cache desired files before its actual demand. The main objective of this work is to study how to minimize the communication latency for vehicles to receive their desired data items. We study non-clustered caching scheme where the optimization problem is formulated to find an optimal caching decision at each RSU. We extend our work by considering clustered caching scheme where RSUs in each cluster cooperate together to serve connected vehicles with minimum latency. Due to the complexity of these problems, we propose a sub-optimal caching policy for each scheme. We compare the performance of the optimal caching policy to that of the sub-optimal caching policy. Numerical results reveal that proactive caching has a great performance gain when compared to the reactive baseline scheme. Furthermore, results manifest that the clustered caching scheme has a significant performance over the non-clustered scheme.
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基于城市模型的车辆自组织网络的主动缓存
路边单元缓存(rsu)是一种很有前途的技术,可以减轻车辆自组网(VANETs)中网络回程的负载。它还允许我们最大限度地减少rsu和联网车辆之间的通信延迟,这些车辆对大量多媒体内容感兴趣。这项工作提出了新的主动缓存方案在城市交通环境的rsu。我们采用了曼哈顿的城市模式,街道以有组织的方式排列,允许移动节点沿着水平和垂直街道的网格穿越。利用有关车辆需求和移动模式的信息可以提高缓存能力,并使我们能够在实际需求之前主动缓存所需的文件。这项工作的主要目的是研究如何最小化车辆接收所需数据项的通信延迟。我们研究了非集群缓存方案,其中的优化问题是在每个RSU上找到一个最优的缓存决策。我们通过考虑集群缓存方案扩展了我们的工作,其中每个集群中的rsu一起合作,以最小的延迟为连接的车辆提供服务。由于这些问题的复杂性,我们为每个方案提出了一个次优缓存策略。我们比较了最优缓存策略和次优缓存策略的性能。数值结果表明,与被动基线方案相比,主动缓存具有很大的性能提升。此外,结果表明集群缓存方案比非集群缓存方案具有显著的性能。
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