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Mathematical Problems in EngineeringVolume 2013 2013, Article ID 830786, 9 pages

Research Article

School of Electronic and Information Engineering, Xi-an Jiaotong University, Xi-an 710049, China

School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China

School of Electronic Engineering, Xi-an Jiaotong University, Xi-an 710049, China

Received 10 January 2013; Revised 7 April 2013; Accepted 26 April 2013

Academic Editor: Engang Tian

Copyright © 2013 Jing Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Due to high efficiency and good scalability, hierarchical hybrid P2P architecturehas drawn more and more attention in P2P streaming research and application fieldsrecently. The problem about super peer selection, which is the key problem in hybridheterogeneous P2P architecture, is becoming highly challenging because super peersmust be selected from a huge and dynamically changing network. A distributed superpeer selection SPS algorithm for hybrid heterogeneous P2P streaming system basedon evolutionary game is proposed in this paper. The super peer selection procedureis modeled based on evolutionary game framework firstly, and its evolutionarily stablestrategies are analyzed. Then a distributed Q-learning algorithm ESS-SPS accordingto the mixed strategies by analysis is proposed for the peers to converge to the ESSsbased on its own payoff history. Compared to the traditional randomly super peer selectionscheme, experiments results show that the proposed ESS-SPS algorithm achievesbetter performance in terms of social welfare and average upload rate of super peers andkeeps the upload capacity of the P2P streaming system increasing steadily with thenumber of peers increasing.





Autor: Jing Chen, Rui-Min Wang, Lei Li, Zhi-Hong Zhang, and Xiao-She Dong

Fuente: https://www.hindawi.com/



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