DocumentCode :
2657916
Title :
Data Scheduling Strategy in P2P VoD System Based on Genetic Algorithm
Author :
Huang, Guimin ; Li, Changliang ; Zhou, Ya ; Bin, Chenzhong
Author_Institution :
Guilin Univ. of Electron. Technol., Guilin, China
fYear :
2011
fDate :
4-6 Nov. 2011
Firstpage :
128
Lastpage :
131
Abstract :
In P2P (Peer-to-Peer) VoD (Video-on-Demand) System, data scheduling strategy is critical to make full use of node resource in P2P network, and it can help optimize user experience as well as system throughput. But for a normal peer how to efficiently schedule media data still remains a challenging task. The kind of problem is NP-hard problem due to the dynamic characteristics of P2P network. This paper presents a novel data scheduling strategy for resolving this problem, called GA scheduling, the major characteristic of which is to adopt genetic algorithm for optimization. Four steps (selection/ crossover/ mutation/ evaluation) are applied iteratively to optimize scheduling effect until stopping condition is met. Several experiments are designed at last on the P2P VoD system. The results demonstrate the effectiveness of the data scheduling strategy proposed in this paper.
Keywords :
data handling; genetic algorithms; peer-to-peer computing; scheduling; video on demand; GA scheduling; NP-hard problem; P2P VoD system; P2P network; data scheduling; data scheduling strategy; genetic algorithm; peer-to-peer system; video-on-demand system; Delay; Genetic algorithms; Media; Peer to peer computing; Scheduling; Servers; Video recording; NP-hard problem; P2P VoD System; data scheduling strategy; genetic algorithm; node resource;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Information Networking and Security (MINES), 2011 Third International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-1795-6
Type :
conf
DOI :
10.1109/MINES.2011.86
Filename :
6103737
Link To Document :
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