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机构地区:[1]河南大学计算机与信息工程学院,开封475004
出 处:《计算机科学》2012年第B06期142-145,共4页Computer Science
基 金:国家自然科学基金青年基金(61103195);中国博士后科学基金面上项目(20100480048);河南省科技攻关项目基金(072102210044;102102210489)资助
摘 要:P2P流媒体直播系统在互联网上显示出了巨大的潜在吸引力,但此类系统的大规模部署严重依赖于它们处理高动态变化的效率,特别是在蜂拥时期。其主要原因是P2P流媒体直播系统的扩展在很大程度上取决于流媒体应用的时间需求。在分析和实验的基础上,提出了系统规模与时间约束的内在联系及其制约因素,构建了一个通用的P2P流媒体系统模型,来集中分析节点在蜂拥时期加入系统的过程。首先说明了简单使用"需求供给"概念模型来描述系统的规模是不够的,然后利用类似Gossip协议的随机伙伴选择机制,推出系统规模随时间变化的上限,在MatlabR2010a平台上比较分析了一些关键性因素的变化对系统扩展的影响。Peer-to-Peer(P2P) live streaming systems have recently shown great potential attractive on the Internet.However,large-scale deployment of such systems relies too much on their efficiency in dealing with high dynamic changes,especially in the flash crowd period.The main reason is that the expansion of a P2P live streaming system largely depends on the of the time demand of streaming media applications.Based on the proposed analysis and experiment,we found the inherent relation between the system scale and the time,as well as the constraints.We constructed a generic model for P2P streaming system to concentrate on analyzing the process that the nodes added to the system in the flash crowd.The paper first argued that simply using the "supply-demand" concept model to describe the system scale is not enough,and then introduced the upper bound of system scale over time with a random partner selection strategy like Gossip protocol.Finally we showed the impact on system scalability by critical factors clearly through a comparative analysis on Matlab R2010a platform.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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