NDLI: Multi-Channel Live P2P Streaming: Refocusing on Servers

Content Provider	IEEE Xplore Digital Library
Author	Chuan Wu Baochun Li Shuqiao Zhao
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON (Chuan Wu; Baochun Li)
Abstract	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.
Starting Page	1355
Ending Page	1363
File Size	794648
Page Count	9
File Format	PDF
ISBN	9781424420254
ISSN	0743166X
DOI	10.1109/INFOCOM.2008.193
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bandwidth Streaming media Demand forecasting Communications Society Peer to peer computing Performance analysis Runtime Clustering algorithms Multimedia communication Topology
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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