DocumentCode :
2041358
Title :
An adaptive stabilization framework for distributed hash tables
Author :
Ghinita, Gabriel ; Teo, Yong Meng
Author_Institution :
Dept. of Comput. Sci., Singapore Nat. Univ., Singapore
fYear :
2006
fDate :
25-29 April 2006
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.
Keywords :
adaptive systems; graph theory; peer-to-peer computing; stability; adaptive stabilization; distributed hash tables; overlay network; peer-to-peer computing; topology graph reorganization; Computer science; Data analysis; Data structures; Distributed computing; Drives; Large-scale systems; Network topology; Peer to peer computing; Routing protocols; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International
Print_ISBN :
1-4244-0054-6
Type :
conf
DOI :
10.1109/IPDPS.2006.1639269
Filename :
1639269
Link To Document :
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