基于节点能力的P2P流媒体推拉结合数据调度算法
首发时间:2011-11-16
摘要:现有P2P流媒体直播系统中缺乏较完善的媒体数据调度算法,导致P2P流媒体直播业务出现启动时延较大及播放连续度较差的问题。提出一种推拉结合的数据调度算法,该算法最大化利用了节点的上传能力,并且针对直播业务实时性较强的特点,在以推模式为主的数据调度过程中,采用拉模式解决媒体播放不连续的问题,使媒体流在最短时间内恢复正常。实验结果表明,基于推拉结合的数据调度算法可以有效缩短直播业务中的启动时延和提升播放连续度,改善了流媒体直播系统中的用户体验。
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A Push-pull Scheduling Algorithm based on Node Capacity in P2P Streaming Systems
Abstract:The lack of good enough media data scheduling algorithm, result in long startup delay and poor continuous playback problems in the P2P streaming live system. This paper presents a push-pull data scheduling algorithm, in which the use of nodes' upload capacity is maximized. With the real-time characteristic of the live system, pull mode plays an important role to help solve the continuous playback problem when the push mode is mainly used, which makes the play of the media recovery in the shortest time. Experimental results show that the push-pull data scheduling algorithm can take an effective aspect in reducing the startup delay and enhance the continuous playback degree, greatly improved the user experience of the live streaming system.
Keywords: peer-to-peer streaming media data scheduling push-pull
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