DocumentCode :
2110514
Title :
Reducing Correlated Failures Impact in Peer-to-Peer Storage Systems Using Mobile Agents Flocks
Author :
Romito, B. ; Bourdon, F.
Author_Institution :
GREYC Lab., Univ. de Caen Basse-Normandie, Caen, France
Volume :
2
fYear :
2012
fDate :
4-7 Dec. 2012
Firstpage :
316
Lastpage :
323
Abstract :
This paper introduces MinCor (Minimum of Correlations), a decentralized simulated annealing algorithm designed for the data placement in peer-to-peer networks. Its goal is to reduce the correlated failures impact in such data storage systems. This data placement is realized using a multi-agent system which turns the documents into mobile agents flocks. After a network clustering step where highly correlated peers are regrouped together, the flocks executing MinCor are able to find a placement minimizing the number of agents on the same clusters. This placement is obtained in a decentralized way thanks to the environment exploration capabilities of the flocks. A set of experiments are performed on this system in presence of correlated failures. They show that, in practice, the expected placement is well obtained. They also show that, flocks using the MinCor algorithm suffer less simultaneous losses in presence of correlated failures than a mere random placement.
Keywords :
mobile agents; peer-to-peer computing; simulated annealing; storage management; MinCor; correlated failure impact; data placement; data storage system; decentralized simulated annealing algorithm; minimum of correlation; mobile agent flocks; network clustering; peer-to-peer network; peer-to-peer storage system; Correlated failures; decentralized data storage; distributed simulated annealing; flocking; mobile agents; peer-to-peer networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
Conference_Location :
Macau
Print_ISBN :
978-1-4673-6057-9
Type :
conf
DOI :
10.1109/WI-IAT.2012.17
Filename :
6511588
Link To Document :
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