实时D2D流媒体网络中激励共享的平均场博弈分析
Incentivizing Sharing in Realtime D2D Streaming Networks: A Mean Field Game Perspective
摘要：
我们考虑的问题，流直播内容的一个集群的协同定位的无线设备，既有一个昂贵的单播基站到设备（B2D）接口，以及一个便宜的广播设备到设备（D2D）接口，可以同时使用。我们的设置是一个流媒体系统，使用逐块随机线性编码方法，以最小的B2D使用率实现准时交付的目标百分比。我们的目标是设计一个激励框架，在确保良好的服务质量的同时，促进跨设备的合作。基于从诚实拍卖中得出的想法，我们设计了一种机制，通过在具有大量设备的环境中进行适当的转移（货币支付或回扣）以及对等到达和离开来实现这一目标。在这里，我们表明，平均场游戏可以用来准确地近似我们的系统。此外，在这种制度下计算最佳对策的复杂性很低。我们在Android测试平台上实现了该系统，并使用真实世界的实验来说明其有效的性能。
英文摘要：
We consider the problem of streaming live content to a cluster of co-located wireless devices that have both an expensive unicast base-station-to-device (B2D) interface, as well as an inexpensive broadcast device-to-device (D2D) interface, which can be used simultaneously. Our setting is a streaming system that uses a block-by-block random linear coding approach to achieve a target percentage of on-time deliveries with minimal B2D usage. Our goal is to design an incentive framework that would promote such cooperation across devices, while ensuring good quality of service. Based on ideas drawn from truth-telling auctions, we design a mechanism that achieves this goal via appropriate transfers (monetary payments or rebates) in a setting with a large number of devices, and with peer arrivals and departures. Here, we show that a Mean Field Game can be used to accurately approximate our system. Furthermore, the complexity of calculating the best responses under this regime is low. We implement the proposed system on an Android testbed, and illustrate its efficient performance using real world experiments.
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