Network Optimization for Large-Scale Content Distribution
Software update and video streaming require massive and/or long-term content distribution. Specifically, new release of content causes steep increase of requests, making the distribution server a bottleneck. To tackle this problem, several systems, e.g., Windows update, recently apply peer-to-peer (P2P) file distribution where clients called peers upload retrieved fragments of the whole content, i.e., pieces, to other peers. However, some peers will not be willing to upload pieces to others, which are called free riders, due to communication overhead. tit-for-tat (TFT) strategy in game theory can suppress such free riding behavior by encouraging equivalent exchange of pieces among each pair of peers. In this research, we analyze the optimal design of the TFT-based P2P file distribution through mathematical optimization (e.g., linear optimization (programming) and integer linear optimization) and analytical models (e.g., flood model).