A Stackelberg Game Approach to Proactive Caching in Large-Scale Mobile Edge Networks
A Stackelberg Game Approach to Proactive Caching in Large-Scale Mobile Edge Networks
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DOI：
10.1109/twc.2018.2839111
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发表时间：
2018-05
影响因子：
10.4
通讯作者：
Zijie Zheng;Lingyang Song;Zhu Han;Geoffrey Ye Li;H. V. Poor
中科院分区：
文献类型：
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作者：
Zijie Zheng;Lingyang Song;Zhu Han;Geoffrey Ye Li;H. V. Poor
在边缘网络的存储中缓存流行文件，即边缘缓存，是服务提供商 (SP) 减少边缘节点 (EN) 冗余回程传输的一种有前景的方法。在拥有大量 EN 和移动用户的 5G 网络中设计有效的边缘缓存激励机制仍然是一个悬而未决的问题。在本文中，研究了一种具有一个 SP、大量 EN 和具有时间相关请求的移动用户的边缘网络。设计了一种用于边缘缓存的收敛且可扩展的Stackelberg游戏。具体来说，游戏被分解为两类子游戏：存储分配游戏（SAG）和多个用户分配游戏（UAG）。提出了一种基于 Stackelberg 博弈的乘子交替方向方法（Stackelberg game-based ADMM），以分布式方式求解 SAG 或每个 UAG。根据分析和仿真结果，收敛速度、整个博弈的最优性以及信息交换量与网络规模呈线性（或次线性）相关，这表明该框架具有应对大规模缓存问题的潜力。所提出的方法还比现有方法需要更少的回程资源。
Caching popular files in the storage of edge networks, namely edge caching, is a promising approach for service providers (SPs) to reduce redundant backhaul transmission to edge nodes (ENs). It is still an open problem to design an efficient incentive mechanism for edge caching in 5G networks with a large number of ENs and mobile users. In this paper, an edge network with one SP, a large number of ENs and mobile users with time-dependent requests is investigated. A convergent and scalable Stackelberg game for edge caching is designed. Specifically, the game is decomposed into two types of sub-games, a storage allocation game (SAG) and a number of user allocation games (UAGs). A Stackelberg game-based alternating direction method of multipliers (Stackelberg game-based ADMM) is proposed to solve either the SAG or each UAG in a distributed manner. Based on both analytical and simulation results, the convergence speed, the optimum of the entire game, and the amount of information exchange are linearly (or sublinearly) related to the network size, which indicates that this framework can potentially cope with large-scale caching problems. The proposed approach also requires less backhaul resource than the existed approaches.