Presentation 2008-11-14
Self-Adaptation of DHT Routing Table Size with Attractor Selection
Rui LIN, Kenji LEIBNITZ, Masayuki MURATA,
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Abstract(in English) In this paper we discuss the self-adaptation of the routing table size of a distributed hash table (DHT) by applying the biologically inspired attractor selection method to adapt to variations in the traffic caused by uncontrollable and unpredictable fluctuations in the underlay network. Since the common DHT mechanisms provide only static settings of the routing table, our goal is to perform an adaptive control, as unsuitable parameter settings would cause too much overhead traffic and deteriorate the overall network performance. We adopt attractor selection as adaptation scheme, since it provides better self-adaptablity and robustness features than other methods and we demonstrate its applicability to control the DHT node state for the case of the routing table size of Pastry, a well-known DHT algorithm. Our goal is to minimize the overhead traffic when the the conditions in the underlay network change.
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Keyword(in English) DHT / Pastry / attractor selection / self-organization / routing table
Paper # NS2008-105
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Committee NS
Conference Date 2008/11/6(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Self-Adaptation of DHT Routing Table Size with Attractor Selection
Sub Title (in English)
Keyword(1) DHT
Keyword(2) Pastry
Keyword(3) attractor selection
Keyword(4) self-organization
Keyword(5) routing table
1st Author's Name Rui LIN
1st Author's Affiliation Osaka University, Graduate School of Information Science and Technology Advanced Network Architecture Laboratory()
2nd Author's Name Kenji LEIBNITZ
2nd Author's Affiliation Osaka University, Graduate School of Information Science and Technology Advanced Network Architecture Laboratory
3rd Author's Name Masayuki MURATA
3rd Author's Affiliation Osaka University, Graduate School of Information Science and Technology Advanced Network Architecture Laboratory
Date 2008-11-14
Paper # NS2008-105
Volume (vol) vol.108
Number (no) 286
Page pp.pp.-
#Pages 6
Date of Issue