DocumentCode :
510118
Title :
A Destination-Oriented Multicast Trees Optimization Algorithm for Controlling P2P Traffic
Author :
Zhao, Yuhui ; An, Yuyan
Author_Institution :
Manage. Dept., Northeast Univ. at Qinhuangdao, Qinhuangdao, China
Volume :
1
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
353
Lastpage :
357
Abstract :
It is necessary to control the P2P traffic among ASs (autonomous systems) while the P2P applications occupy the most bandwidth of the backbone network. Instead of only restricting the P2P applications, the paper suggests an intelligent relay method based on P2P communities model. The proxy of content caching (PCC) nodes is proposed which are used to manage the local content cache in the P2P communities. The problems of building the core overlay multicast tree (COMT) among the PCC nodes can be reduced to the minimal steiner tree problem (MSTP). For optimizing the multicast trees, the off-line genetic algorithm (GA) is adopted, which uses the destination-oriented method for represent chromosomes and genetic operators. Simulation experimental results show that our model can obtain a near optimal solution for COMT, which has the feathers of low bandwidth cost and high scalability.
Keywords :
genetic algorithms; peer-to-peer computing; telecommunication traffic; trees (mathematics); P2P traffic; autonomous systems; core overlay multicast tree; destination-oriented for method; destination-oriented multicast trees optimization algorithm; genetic algorithm; minimal steiner tree problem; proxy of content caching nodes; Bandwidth; Communication system traffic control; Content management; Control systems; Genetic algorithms; Multicast algorithms; Optimization methods; Relays; Spine; Traffic control; Core Overlay Multicast Tree; Genetic Algorithm(GA); P2P; QoS-sensitive; multicast trees optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.428
Filename :
5376223
Link To Document :
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