Please use this identifier to cite or link to this item: https://doi.org/10.1109/IPDPS.2006.1639269
Title: An adaptive stabilization framework for distributed hash tables
Authors: Ghinita, G.
Yong, M.T. 
Issue Date: 2006
Source: Ghinita, G.,Yong, M.T. (2006). An adaptive stabilization framework for distributed hash tables. 20th International Parallel and Distributed Processing Symposium, IPDPS 2006 2006. ScholarBank@NUS Repository. https://doi.org/10.1109/IPDPS.2006.1639269
Abstract: Distributed Hash Tables (DHT) algorithms obtain good lookup performance bounds by using deterministic rules to organize peer nodes into an overlay network. To preserve the invariants of the overlay network, DHTs use stabilization procedures that reorganize the topology graph when participating nodes join or fail. Most DHTs use periodic stabilization, in which peers perform stabilization at fixed intervals of time, disregarding the rate of change in overlay topology; this may lead to poor performance and large stabilization-induced communication overhead. We propose a novel adaptive stabilization framework that takes into consideration the continuous evolution in network conditions. Each peer collects statistical data about the network and dynamically adjusts its stabilization rate based on the analysis of the data. The objective of our scheme is to maintain nominal network performance and to minimize the communication overhead of stabilization. © 2006 IEEE.
Source Title: 20th International Parallel and Distributed Processing Symposium, IPDPS 2006
URI: http://scholarbank.nus.edu.sg/handle/10635/41685
ISBN: 1424400546
DOI: 10.1109/IPDPS.2006.1639269
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

13
checked on Dec 13, 2017

Page view(s)

57
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.