论文摘要
由于Sopcast,、PPlive、Youku等流媒体应用的蓬勃发展,流媒体内容分发在互联网上迅速普及,取得巨大的成功。上述应用大多采用客户机/服务器(C/S)模型,消耗了大量的服务器带宽资源和存储容量。为了克服上述限制,提出了很多对等网络(P2P)流媒体系统以实现可扩展和成本合算的内容分发策略。P2P流媒体系统中的一个关键问题是如何将有限的资源分配给大量的节点,以确保数据的有效性、减小启动时延、提高播放连续度。本论文提出一种基于流的内容分发模型,以描述P2P流媒体网络系统中数据块分发过程。本模型考虑对等节点辅助环境下的数据块分发过程。数据块分发相互独立,由于对等节点尽早获取数据块的竞争产生冲突。本文提出当带宽足够时新的下载者加入系统:状态为上传的节点为新下载者提供其内存中的共享内容块。为了对此进行控制,对服务器资源的竞争激烈时,可让靠近源服务器的对等节点从服务器获取数据块,然后向其它对等节点贡献其资源,从而像共享节点一样辅助服务器;系统由此最大化共享节点的数量,使得视频流播放平顺。这一策略通过避免不当的带宽分配以接入新的节点,其中已有对等节点协助获得较好的视频点播性能。所提出的内容数据分发模型表明,随机指数退避关于对等节点数目呈现出良好的可扩展性,并能以接近最优的方式分发数据块。本文提出的模型和参数估计对于对等网络流媒体系统的设计和运营过程中提高用户体验相关性能有着重要的意义。
论文目录
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