Mobile Edge Caching is a promising technique to enhance the content delivery quality and reduce the backhaul link congestion, by storing popular content at the network edge or mobile devices (e.g. base stations and smartphones) that are proximate to content requesters. In this work, we study a novel mobile edge caching framework, which enables mobile devices to cache and share popular contents with each other via device-to-device (D2D) links. We are interested in the following incentive problem of mobile device users: whether and which users are willing to cache and share what contents, taking the user mobility and cost/reward into consideration. The problem is challenging in a large-scale network with a large number of users. We introduce the evolutionary game theory, an effective tool for analyzing large-scale dynamic systems, to analyze the mobile users' content caching and sharing strategies. Specifically, we first derive the users' best caching and sharing strategies, and then analyze how these best strategies change dynamically over time, based on which we further characterize the system equilibrium systematically. Simulation results show that the proposed caching scheme outperforms the existing schemes in terms of the total transmission cost and the cellular load. In particular, in our simulation, the total transmission cost can be reduced by 42.5%-55.2% and the cellular load can be reduced by 21.5%-56.4%.

中文翻译：

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激励移动边缘缓存和共享：一种进化的游戏方法

移动边缘缓存是一种很有前途的技术，通过将流行内容存储在网络边缘或靠近内容请求者的移动设备（例如基站和智能手机），可以提高内容交付质量并减少回程链路拥塞。在这项工作中，我们研究了一种新颖的移动边缘缓存框架，该框架使移动设备能够通过设备到设备 (D2D) 链接缓存和共享流行内容。我们对移动设备用户的以下激励问题感兴趣：是否以及哪些用户愿意缓存和共享哪些内容，同时考虑用户的移动性和成本/回报。该问题在拥有大量用户的大规模网络中具有挑战性。我们介绍了进化博弈论，这是一种分析大规模动态系统的有效工具，分析移动用户的内容缓存和共享策略。具体来说，我们首先推导出用户的最佳缓存和共享策略，然后分析这些最佳策略如何随时间动态变化，在此基础上我们进一步系统地刻画系统均衡。仿真结果表明，所提出的缓存方案在总传输成本和蜂窝负载方面优于现有方案。特别是，在我们的模拟中，总传输成本可以降低 42.5%-55.2%，蜂窝负载可以降低 21.5%-56.4%。在此基础上，我们进一步系统地刻画了系统平衡。仿真结果表明，所提出的缓存方案在总传输成本和蜂窝负载方面优于现有方案。特别是，在我们的模拟中，总传输成本可以降低 42.5%-55.2%，蜂窝负载可以降低 21.5%-56.4%。在此基础上，我们进一步系统地刻画了系统平衡。仿真结果表明，所提出的缓存方案在总传输成本和蜂窝负载方面优于现有方案。特别是，在我们的模拟中，总传输成本可以降低 42.5%-55.2%，蜂窝负载可以降低 21.5%-56.4%。