Nash bargaining between friends for cooperative data distribution in a social peer-to-peer swarming system

Guilin Wang; Haojun Zhang; Yanqin Zhu; Qijin Ji; Haifeng Shen

doi:10.1109/ICMLC.2013.6890840

Nash bargaining between friends for cooperative data distribution in a social peer-to-peer swarming system

Guilin Wang, Haojun Zhang, Yanqin Zhu, Qijin Ji, Haifeng Shen

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

Abstract

Online social networks and peer-to-peer (P2P) data swarming are a natural match, but a significant distinction between a traditional P2P swarming system and its social version is the social ties among peers which suppress the free riding behavior and make cooperation among peers feasible. In this paper, we present a game theoretical formulation for cooperative data distribution based on friend coalitions in a social P2P swarming system and derive a Nash bargaining solution for a two-player bargaining game with the analysis of Pareto optimality and fairness. Both our analytical and experimental results show that the proposed strategies can effectively stimulate cooperation among peers and significantly improve the efficiency and fairness of data distribution compared to the traditional non-cooperative P2P swarming systems.

Original language	English
Pages	1490-1495
Number of pages	6
DOIs	https://doi.org/10.1109/ICMLC.2013.6890840
Publication status	Published - 1 Jan 2013
Event	The 2013 IEEE International Conference on Machine Learning and Cybernetics - Duration: 14 Jul 2013 → …

Conference

Conference	The 2013 IEEE International Conference on Machine Learning and Cybernetics
Period	14/07/13 → …

Keywords

cooperative data distribution
Nash bargaining solution
Online social networks
P2P swarming

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10.1109/ICMLC.2013.6890840

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Nash bargaining between friends for cooperative data distribution in a social peer-to-peer swarming system

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Keywords

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