DocumentCode :
617908
Title :
A diffusion-based ACO resource discovery framework for dynamic p2p networks
Author :
Krynicki, Kamil ; Jaen, Javier ; Catala, A.
Author_Institution :
Dept. de Sist. Informaticos y Comput., Univ. Politec. de Valencia, Valencia, Spain
fYear :
2013
fDate :
20-23 June 2013
Firstpage :
860
Lastpage :
867
Abstract :
The Ant Colony Optimization (ACO) has been a very resourceful metaheuristic over the past decade and it has been successfully used to approximately solve many static NP-Hard problems. There is a limit, however, of its applicability in the field of p2p networks; derived from the fact that such networks have the potential to evolve constantly and at a high pace, rendering the already-established results useless. In this paper we approach the problem by proposing a generic knowledge diffusion mechanism that extends the classical ACO paradigm to better deal with the p2p´s dynamic nature. Focusing initially on the appearance of new resources in the network we have shown that it is possible to increase the efficiency of ant routing by a significant margin.
Keywords :
ant colony optimisation; peer-to-peer computing; resource allocation; ant colony optimization; ant routing; diffusion-based ACO resource discovery framework; dynamic P2P networks; generic knowledge diffusion mechanism; metaheuristic; static NP-hard problem; Algorithm design and analysis; Convergence; Heuristic algorithms; Resource management; Routing; Semantics; Strain; ACO; Ant Colony Optimization; Overlay Networks; Semantic Networks; Semantic Search; p2p;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
Type :
conf
DOI :
10.1109/CEC.2013.6557658
Filename :
6557658
Link To Document :
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