• DocumentCode
    760802
  • Title

    Node Isolation Model and Age-Based Neighbor Selection in Unstructured P2P Networks

  • Author

    Yao, Zhongmei ; Wang, Xiaoming ; Leonard, Derek ; Loguinov, Dmitri

  • Author_Institution
    Dept. of Comput. Sci., Texas A&M Univ., College Station, TX
  • Volume
    17
  • Issue
    1
  • fYear
    2009
  • Firstpage
    144
  • Lastpage
    157
  • Abstract
    Previous analytical studies of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared with uniform selection of neighbors. In fact, the second strategy based on random walks on age-proportional graphs demonstrates that, for lifetimes with infinite variance, the system monotonically increases its resilience as its age and size grow. Specifically, we show that the probability of isolation converges to zero as these two metrics tend to infinity. We finish the paper with simulations in finite-size graphs that demonstrate the effect of this result in practice.
  • Keywords
    graph theory; peer-to-peer computing; probability; random processes; telecommunication network reliability; age-proportional graphs; arbitrary age-biased neighbor-selection algorithm; exponential user lifetimes; finite-size graphs; graph partitioning; heavy-tailed user lifetimes; node-isolation model; probability; random walks; residual lifetimes; unstructured P2P network resilience; user isolation; Age-based selection; heavy-tailed lifetimes; node isolation; peer-to-peer networks; user churn;
  • fLanguage
    English
  • Journal_Title
    Networking, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6692
  • Type

    jour

  • DOI
    10.1109/TNET.2008.925626
  • Filename
    4547464