A diffusion-based ACO resource discovery framework for dynamic p2p networks
Autor: | Javier Jaen, Alejandro Catala, Kamil Krynicki |
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Rok vydání: | 2013 |
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Zdroj: | IEEE Congress on Evolutionary Computation RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
DOI: | 10.1109/cec.2013.6557658 |
Popis: | 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. Kamil Krynicki is supported by a FPI fellowship from the Universitat Politècnica de València with reference number 3117. This work received financial support from the Spanish Ministry of Education under the National Strategic Program of Research and Project TSI2010-20488. |
Databáze: | OpenAIRE |
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