Using Aggregation for Adaptive Super-Peer Discovery on the Gradient Topology

  • Jan Sacha
  • Jim Dowling
  • Raymond Cunningham
  • René Meier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3996)


Peer-to-peer environments exhibit a very high diversity in individual peer characteristics ranging by orders of magnitude in terms of uptime, available bandwidth, and storage space. Many systems attempt to exploit this resource heterogeneity by using the best performing and most reliable peers, called super-peers, for hosting system services. However, due to inherent decentralisation, scale, dynamism, and complexity of P2P environments, self-managing super-peer selection is a challenging problem. In this paper, decentralised aggregation techniques are used to reduce the uncertainty about system properties by approximating the peer utility distribution allowing peers to calculate adaptive thresholds in order to discover appropriate super-peers. Furthermore, a heuristic search algorithm is described that allows super-peers, above a certain utility threshold, to be efficiently discovered and utilised by any peer in the system.


Overlay Network Aggregation Algorithm Gradient Search Utility Threshold Gradient Topology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jan Sacha
    • 1
  • Jim Dowling
    • 1
  • Raymond Cunningham
    • 1
  • René Meier
    • 1
  1. 1.Distributed Systems GroupTrinity CollegeDublinRepublic of Ireland

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