P2P流媒体系统中基于相关窗口的缓冲区映射消息压缩
Buffer Map Message Compression Based on Relevant Window in P2P Streaming Media System
摘要：
流行的对等流媒体系统，如PPLive和UUSee，依赖于对等体之间的定期缓冲区映射交换，以实现正确的操作。缓冲区映射交换包含冗余信息，这会导致不可忽略的开销。在本文中，我们提出了一个理论框架，研究如何可以降低开销。与传统的数据压缩方法不同的是，我们不把每个缓冲区映射作为一个孤立的数据块，而是考虑顺序交换的缓冲区映射之间的相关性。在此框架下，提出了两种缓冲映射压缩方案，并从数学上证明了方案的正确性。此外，我们推导了基于概率论和信息论的压缩增益的理论极限。基于UUSee（一种流行的P2P流媒体平台）的系统参数，我们的模拟表明，应用我们的方案后，缓冲区映射大小分别减少了86%和90%（从456位减少到仅66位和46位）。此外，通过与传统的压缩方法（对单个块）相结合，大小分别减少了91%和95%（到42位和24位）。本文的研究为开发实用的压缩算法提供了指导。
英文摘要：
Popular peer to peer streaming media systems such as PPLive and UUSee rely on periodic buffer-map exchange between peers for proper operation. The buffer-map exchange contains redundant information which causes non-negligible overhead. In this paper we present a theoretical framework to study how the overhead can be lowered. Differentiating from the traditional data compression approach, we do not treat each buffer-map as an isolated data block, but consider the correlations between the sequentially exchanged buffer-maps. Under this framework, two buffer-map compression schemes are proposed and the correctness of the schemes is proved mathematically. Moreover, we derive the theoretical limit of compression gain based on probability theory and information theory. Based on the system parameters of UUSee (a popular P2P streaming platform), our simulations show that the buffer-map sizes are reduced by 86% and 90% (from 456 bits down to only 66 bits and 46 bits) respectively after applying our schemes. Furthermore, by combining with the traditional compression methods (on individual blocks), the sizes are decreased by 91% and 95% (to 42 bits and 24 bits) respectively. Our study provides a guideline for developing practical compression algorithms.
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