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Hit Ratio Driven Mobile Edge Caching Scheme for Video on Demand Services

机译:视频点播服务的命中率驱动的移动边缘缓存方案

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More and more scholars focus on mobile edge computing (MEC) technology, because the strong storage and computing capabilities of MEC servers can reduce the long transmission delay, bandwidth waste, energy consumption, and privacy leaks in the data transmission process. In this paper, we study the cache placement problem to determine how to cache videos and which videos to be cached in a mobile edge computing system. First, we derive the video request probability by taking into account video popularity, user preference and the characteristic of video representations. Second, based on the acquired request probability, we formulate a cache placement problem with the objective to maximize the cache hit ratio subject to the storage capacity constraints. Finally, in order to solve the formulated problem, we transform it into a grouping knapsack problem and develop a dynamic programming algorithm to obtain the optimal caching strategy. Simulation results show that the proposed algorithm can greatly improve the cache hit ratio.
机译:越来越多的学者专注于移动边缘计算(MEC)技术,因为MEC服务器的强大存储和计算能力可以减少数据传输过程中的长传输延迟,带宽浪费,能耗和隐私泄漏。在本文中,我们研究了缓存放置问题,以确定如何在移动边缘计算系统中缓存视频以及哪些视频。首先,我们通过考虑视频普及,用户偏好和视频表示的特征来派生视频请求概率。其次,基于所获取的请求概率,我们配制备高速缓存放置问题,其目的是最大化对存储容量约束的缓存命中率。最后,为了解决配制的问题,我们将其转换为分组背包问题,并开发动态编程算法以获得最佳缓存策略。仿真结果表明,该算法可以大大提高缓存命中率。

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