交叉口车辆网络的协同边缘缓存

Canliang Liao, Chang Liu, Zheng Xue, Yang Liu, G. Han
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引用次数: 0

摘要

随着智能汽车的普及和B5G/6G通信技术的快速发展,各种强大的应用都需要基于车载自组网的协同边缘缓存,以低传输延迟的方式支持海量数据传输。然而,由于车辆网络拓扑结构的高度动态性和边缘服务器存储容量的有限性,设计有效的高速缓存方案是一项挑战,特别是在道路交叉口高速缓存方案的复杂性和灵活性。在本文中,我们提出了一个在双车道道路的四路交叉口的合作边缘缓存方案,以减少内容的平均下载延迟,该方案允许车辆从路边单元(rsu)或基站(BSs)获取内容。为了描述移动车辆与rsu之间通信速率的变化,我们将rsu的覆盖区域划分为不同的通信区域,并在此基础上数学推导了请求内容的平均下载延迟。在此基础上,提出了一种基于动态规划(DP)的非线性整数规划(NLIP)算法来求解协作内容布局优化问题。仿真结果表明,与基于流行度的缓存放置方案和随机缓存放置方案等基准方案相比,所提出的基于dp的协作缓存放置方案在降低平均下载延迟方面更有效。
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Cooperative Edge Caching for Vehicular Networks in Road Intersections
Cooperative edge caching in vehicular ad hoc net-works is expected to support massive data transmissions with low transmission delays, which is required in various powerful applications brought by the proliferation of smart vehicles and rapid development of B5G/6G communication techniques. How-ever, due to highly dynamic topology of vehicular networks and constrained storage capacities of edge servers, the design of effective caching scheme is challenging, especially in road intersections because of its complexity and flexibility. In this paper, we propose a cooperative edge caching scheme in a four-way intersection of two-lane roads to reduce the average download delay of content, which allows vehicles to fetch contents from road side units (RSUs) or base stations (BSs). To characterize the variation of communication rates between moving vehicles and RSUs, we divide coverage areas of RSUs into different communication zones, based on which we mathematically derived the average download delay of requested contents. Then we formulated an optimization problem of cooperative content placement to minimize the overall download delay, and proposed a dynamic programming (DP)-based algorithm to solve this nonlinear integer programming (NLIP) problem. Simulation results show that the proposed DP-based cooperative caching placement scheme is more efficient for average download delay reduction compared with benchmark schemes such as a popularity-based caching placement scheme and a random caching placement scheme.
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