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首页> 外文期刊>Networking, IEEE/ACM Transactions on >A Social-Network-Aided Efficient Peer-to-Peer Live Streaming System
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A Social-Network-Aided Efficient Peer-to-Peer Live Streaming System

机译:社交网络辅助的高效点对点实时流媒体系统

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摘要

In current peer-to-peer (P2P) live streaming systems, nodes in a channel form a P2P overlay for video sharing. To watch a new channel, a node depends on the centralized server to join in the overlay of the channel. In today's live streaming applications, the increase in the number of channels triggers users' desire of watching multiple channels successively or simultaneously. However, the support of such watching modes in current applications is no better than joining in different channel overlays successively or simultaneously through the centralized server, which if widely used, poses a heavy burden on the server. In order to achieve higher efficiency and scalability, we propose a Social-network-Aided efficient liVe strEaming system (SAVE). SAVE regards users' channel switching or multichannel watching as interactions between channels. By collecting the information of channel interactions, nodes' interests, and watching times, SAVE forms nodes in multiple channels with frequent interactions into an overlay, constructs bridges between overlays of channels with less frequent interactions, and enables nodes to identify friends sharing similar interests and watching times. Thus, a node can connect to a new channel while staying in its current overlay, using bridges or relying on its friends, reducing the need to contact the centralized server. We further propose the channel-closeness-based chunk-pushing strategy and capacity-based chunk provider selection strategy to enhance the system performance. Extensive experimental results from the PeerSim simulator and PlanetLab verify that SAVE outperforms other systems in system efficiency and server load reduction, as well as the effectiveness of the two proposed strategies.
机译:在当前的点对点(P2P)实时流系统中,通道中的节点形成用于视频共享的P2P覆盖。为了观看新频道,一个节点依赖中央服务器来加入频道的覆盖范围。在当今的实时流媒体应用中,频道数量的增加触发了用户连续或同时观看多个频道的愿望。然而,在当前应用中对这种观看模式的支持并不比通过集中式服务器相继或同时加入不同的频道覆盖更好,如果广泛使用,则给服务器带来沉重的负担。为了实现更高的效率和可扩展性,我们提出了一种社交网络辅助的有效生活学习系统(SAVE)。 SAVE将用户的频道切换或多频道观看视为频道之间的交互。通过收集频道互动,节点的兴趣和观看时间的信息,SAVE将频繁互动的多个频道中的节点形成一个叠加层,在互动频率较低的频道的叠加层之间架起桥梁,并使节点能够识别具有相同兴趣和兴趣的朋友。看时间。因此,节点可以使用网桥或依靠其朋友而在停留在其当前覆盖图中的同时连接到新通道,从而减少了与集中式服务器联系的需求。我们还提出了基于通道关闭性的块推送策略和基于容量的块提供者选择策略,以提高系统性能。 PeerSim模拟器和PlanetLab的大量实验结果证明,SAVE在系统效率和服务器负载减少以及这两种建议策略的有效性方面均优于其他系统。

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