Multi-Channel Live P2P Streaming: Refocusing on Servers
Multi-Channel Live P2P Streaming: Refocusing on Servers
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DOI：
10.1109/infocom.2008.193
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发表时间：
2008-04
期刊：
影响因子：
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通讯作者：
Chuan Wu;Baochun Li;Shuqiao Zhao
中科院分区：
文献类型：
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作者：
Chuan Wu;Baochun Li;Shuqiao Zhao
由于实时点对点(P2P)流传输信道中的对等点不稳定和时变的对等点上传带宽可用性，最好在专用流传输服务器上提供足够水平的稳定上传能力，以便保证所有信道中的流传输质量。大多数商业P2P流媒体系统都采取了在流媒体服务器上过度提供上传容量的做法。在本文中，我们对商业P2P流媒体系统UUSee的400 GB和7个月的运行跟踪进行了详细的分析，发现流媒体服务器上的可用容量无法跟上数百个频道日益增长的需求。我们提出了一种新的在线服务器容量分配算法，该算法主动调整每个并发通道可用的服务器容量，使每个通道中的服务器带宽供应动态适应预测的需求，同时考虑节点数量、流质量和通道的优先级。该算法能够随着时间的推移而学习，并具有完全的运营商感知能力，以最大限度地将P2P流量限制在ISP边界内。为了评估我们的解决方案的有效性，我们的实验研究是基于该算法的实现，使用P2P流媒体流量的实际通道，并在服务器集群中重放真实世界的跟踪。
Due to peer instability and time-varying peer upload bandwidth availability in live peer-to-peer (P2P) streaming channels, it is preferable to provision adequate levels of stable upload capacities at dedicated streaming servers, in order to guarantee the streaming quality in all channels. Most commercial P2P streaming systems have resorted to the practice of over-provisioning upload capacities on streaming servers. In this paper, we have performed a detailed analysis on 400 GB and 7 months of run-time traces from UUSee, a commercial P2P streaming system, and observed that available capacities on streaming servers are not able to keep up with the increasing demand imposed by hundreds of channels. We propose a novel online server capacity provisioning algorithm that proactively adjusts the server capacities available to each of the concurrent channels, such that the supply of server bandwidth in each channel dynamically adapts to the forecasted demand, taking into account the number of peers, the streaming quality, and the priorities of channels. The algorithm is able to learn over time, and has full ISP awareness to maximally constrain P2P traffic within ISP boundaries. To evaluate the effectiveness of our solution, our experimental studies are based on an implementation of the algorithm with actual channels of P2P streaming traffic, with real-world traces replayed within a server cluster.