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Study of Self-adaptive Strategy Based Incentive Mechanism in Structured P2P System

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Intelligent Computing Methodologies (ICIC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9773))

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Abstract

P2P systems provide peers a dynamic and distributed environment to share resource. Only if peers are voluntarily share with each other can system stably exist. However, peers in such systems are selfish and never want to share even with tiny cost. This can lead to serious free-riding problems. Incentive mechanisms based on evolutionary game aim at designing new strategies to distinguish defective peers from cooperative peers and induce them to cooperate more. Nevertheless, the behavior patterns of peers are versatile. Using only one certain strategy to depict peers’ behaviors is incomplete. In this paper, we propose an adaptive strategy which integrates advantages of 3 classic strategies. These 3 strategies form a knowledge base. Each time a peer with this strategy can select one adjusting to system status according to the adaptive function. Through experiments, we find that in structured system, this strategy can not only promote cooperation but also the system performance.

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Acknowledgments

This paper is supported by the National Science Foundation of China under grant No. 61272173, 61403059.

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Authors and Affiliations

  1. School of Software, Dalian University of Technology, Dalian, 16621, Liaoning, China

    Kun Lu, Shiyu Wang, Ling Xie & Mingchu Li

Authors
  1. Kun Lu
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  2. Shiyu Wang
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  3. Ling Xie
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  4. Mingchu Li
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Corresponding author

Correspondence to Mingchu Li .

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Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. Inha University , Incheon, Korea (Republic of)

    Kyungsook Han

  3. Liverpool John Moores University , Liverpool, United Kingdom

    Abir Hussain

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© 2016 Springer International Publishing Switzerland

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Lu, K., Wang, S., Xie, L., Li, M. (2016). Study of Self-adaptive Strategy Based Incentive Mechanism in Structured P2P System. In: Huang, DS., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2016. Lecture Notes in Computer Science(), vol 9773. Springer, Cham. https://doi.org/10.1007/978-3-319-42297-8_61

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  • DOI: https://doi.org/10.1007/978-3-319-42297-8_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42296-1

  • Online ISBN: 978-3-319-42297-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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