Using Aggregation for Adaptive Super-Peer Discovery on the Gradient Topology
Citation:
J. Sacha, J. Dowling, R. Cunningham, and R. Meier, Using Aggregation for Adaptive Super-Peer Discovery on the Gradient Topology, 2nd IEEE International Workshop on Self-Managed Networks, Systems & Services (SelfMan 2006), Dublin, Ireland, LNCS 3996, Springer-Verlag, 2006, 73 - 86Download Item:
Abstract:
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.
Author's Homepage:
http://people.tcd.ie/rmeierDescription:
PUBLISHED
Author: MEIER, RENE
Publisher:
Springer-VerlagType of material:
Conference PaperCollections
Series/Report no:
LNCS 3996;Availability:
Full text availableKeywords:
Computer science, super-peersMetadata
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