Topology optimization in multi-tree based P2P streaming system

Chao Liang, Yong Liu, Keith W. Ross

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, Peer-to-Peer (P2P) technology has been demonstrated tremendously effective in delivering large-scale video streaming services. Although P2P streaming is scalable and robust, the network-oblivious peering and scheduling in the current designs impede the further improvement in streaming quality and the efficient usage of network resources. New P2P streaming systems exploit network information provided by Internet Service Providers (ISPs) to achieve a higher level of application performance and generate lower traffic stress. In this paper, utilizing information from ISPs, we investigate the strategies on the topology construction and maintenance of multi-tree based P2P streaming systems. We study topology optimization to minimize the average height of sub-stream trees and the average propagation latency in each tree. We first present the optimization formulations, and then propose a set of heuristic algorithms for the construction and dynamic management of the multiple sub-stream trees for practical implementation. Through numerical comparison study, we show that our algorithms can significantly improve the delay performance of existing P2P streaming systems.

Original languageEnglish (US)
Title of host publicationICTAI 2009 - 21st IEEE International Conference on Tools with Artificial Intelligence
Pages806-813
Number of pages8
DOIs
StatePublished - 2009
Event21st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2009 - Newark, NJ, United States
Duration: Nov 2 2009Nov 5 2009

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)1082-3409

Other

Other21st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2009
Country/TerritoryUnited States
CityNewark, NJ
Period11/2/0911/5/09

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Science Applications

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