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An Efficient Adaptive Neighbor Selection Algorithm in Pear-to-Pear Networks

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Cloud Computing (CloudComp 2013)

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Abstract

Based on analysis of fixed random neighbor selection algorithms, this paper presents an efficient adaptive and dynamic neighbor selection algorithm. The new algorithm adopts a comprehensive impact value to measure nodes. The different nodes have different impact values and have different transmission abilities. The nodes with bigger impact values can do more work in P2P system and thus are easier to be selected as neighbors. Simulations show that the new algorithm can reduce the transmission delay and improve the performance of P2P networks.

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Authors and Affiliations

  1. Guangdong Industrial Technical College, Guangzhou, Guangdong, China

    Xian Li & Aili Zhang

Authors
  1. Xian Li
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  2. Aili Zhang
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Corresponding author

Correspondence to Xian Li .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, The University of British Columbia, Vancouver, British Columbia, Canada

    Victor C.M. Leung

  2. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Min Chen

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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, X., Zhang, A. (2014). An Efficient Adaptive Neighbor Selection Algorithm in Pear-to-Pear Networks. In: Leung, V., Chen, M. (eds) Cloud Computing. CloudComp 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 133. Springer, Cham. https://doi.org/10.1007/978-3-319-05506-0_24

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  • DOI: https://doi.org/10.1007/978-3-319-05506-0_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05505-3

  • Online ISBN: 978-3-319-05506-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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