Abstract
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing the training of the neural network. This training is very challenging due to the large number of weights and noise caused by the dynamic neural network testing. The AGLMA is a memetic algorithm consisting of an evolutionary framework which adaptively employs two local searchers having different exploration logic and pivot rules. Furthermore, the AGLMA makes an adaptive noise compensation by means of explicit averaging on the fitness values and a dynamic population sizing which aims to follow the necessity of the optimization process. The numerical results demonstrate that the proposed computational intelligence approach leads to an efficient resource discovery strategy and that the AGLMA outperforms two classical resource discovery strategies as well as a popular neural network training algorithm.
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References
Yang, B., Garcia-Molina, H.: Improving search in peer-to-peer networks. In: Proc. of the 22nd Intern. Conf. on Distributed Computing Systems, pp. 5–14 (2002)
Lv, Q., Cao, P., Cohen, E., Li, K., Shenker, S.: Search and replication in unstructured peer-to-peer networks. In: Proc. of the 16th ACM Intern. Conf. on Supercomputing, pp. 84–95 (2002)
Kalogeraki, V., Gunopulos, D., Zeinalipour-Yazti, D.: A local search mechanism for peer-to-peer networks. In: Proc. 11th ACM Intern. Conf. on Information and Knowledge Management, pp. 300–307 (2002)
Menascé, D.A.: Scalable p2p search. IEEE Internet Computing 7(2), 83–87 (2003)
Tsoumakos, D., Roussopoulos, N.: Adaptive probabilistic search for peer-to-peer networks. In: Proc. 3rd IEEE Intern. Conf. on P2P Computing, pp. 102–109 (2003)
Crespo, A., Garcia-Molina, H.: Routing indices for peer-to-peer systems. In: Proc. of the 22nd IEEE Intern. Conf. on Distributed Computing Systems. pp. 23–33 (2002)
Sarshar, N., Boykin, P.O., Roychowdhury, V.P.: Percolation search in power law networks: Making unstructured peer-to-peer networks scalable. In: Proc. of the IEEE 4th Intern. Conf. on P2P Computing, pp. 2–9 (2004)
Vapa, M., Kotilainen, N., Auvinen, A., Kainulainen, H., Vuori, J.: Resource discovery in p2p networks using evolutionary neural networks. In: Intern. Conf. on Advances in Intelligent Systems - Theory and Applications, 067-04. (2004)
Engelbrecht, A.: Computational Intelligence-An Introduction. J. Wiley, New York, NY (2002)
Kotilainen, N., Vapa, M., Keltanen, T., Auvinen, A., Vuori, J.: P2prealm - peer-to-peer network simulator. In: IEEE Intern. Works. on Computer-Aided Modeling, Analysis and Design of Communication Links and Networks, pp. 93–99 (2006)
Chellapilla, K., Fogel, D.: Evolving neural networks to play checkers without relying on expert knowledge. IEEE Trans. Neural Networks 10(6), 1382–1391 (1999)
Chellapilla, K., Fogel, D.: Evolving an expert checkers playing program without using human expertise. IEEE Trans. Evol. Computation 5(4), 422–428 (2001)
Jin, Y., Branke, J.: Evolutionary optimization in uncertain environments - a survey. IEEE Transactions on Evolutionary Computation 9(3), 303–317 (2005)
Neri, F., Cascella, G.L., Salvatore, N., Kononova, A.V., Acciani, G.: Prudent-daring vs tolerant survivor selection schemes in control design of electric drives. In: Rothlauf, F., Branke, J., Cagnoni, S., Costa, E., Cotta, C., Drechsler, R., Lutton, E., Machado, P., Moore, J.H., Romero, J., Smith, G.D., Squillero, G., Takagi, H. (eds.) EvoWorkshops 2006. LNCS, vol. 3907, pp. 805–809. Springer, Berlin Heidelberg New York (2006)
Krasnogor, N.: Toward robust memetic algorithms. In: Hart, W.E. et al. (ed.) Recent Advances in Memetic Algorithms, pp. 185–207. Springer, Berlin Heidelberg, New York (2004)
Cerny, V.: A thermodynamical approach to the traveling salesman problem. Theory and Applications 45(1), 41–51 (1985)
Hooke, R., Jeeves, T.A.: Direct search solution of numerical and statistical problems. Journal of the ACM 8, 212–229 (1961)
Neri, F., Toivanen, J., Cascella, G.L., Ong, Y.S.: An adaptive multimeme algorithm for designing hiv multidrug therapies. IEEE/ACM Transactions on Computational Biology and Bioinformatics, Special Issue on Computational Intelligence Approaches in Computational Biology and Bioinformatics (2007) (to appear)
Caponio, A., Cascella, G.L., Neri, F., Salvatore, N., Sumner, M.: A fast adaptive memetic algorithm for on-line and off-line control design of PMSM drives. IEEE Trans. on System Man. and Cybernetics-part B. 37(1), 28–41 (2007)
Neri, F., Toivanen, J., Mäkinen, R.A.E.: An adaptive evolutionary algorithm with intelligent mutation local searchers for designing multidrug therapies for HIV. Springer, Berlin Heidelberg New York (2007)
Neri, F., Mäkinen, R.A.E.: Hierarchical evolutionary algorithms and noise compensation via adaptation. In: Yang, S. et al. (ed.) Evolutionary Computation in Dynamic and Uncertain Environments, Springer, Berlin Heidelberg, New York (2007)
Miller, B.L., Goldberg, D.E.: Genetic algorithms, selection schemes, and the varying effects of noise. Evolutionary Computation 4(2), 113–131 (1996)
Schmidt, C., Branke, J., Chick, S.E.: Integrating techniques from statistical ranking into evolutionary algorithms. In: Rothlauf, F., Branke, J., Cagnoni, S., Costa, E., Cotta, C., Drechsler, R., Lutton, E., Machado, P., Moore, J.H., Romero, J., Smith, G.D., Squillero, G., Takagi, H. (eds.) EvoWorkshops 2006. LNCS, vol. 3907, pp. 752–763. Springer, Berlin Heidelberg New York (2006)
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Neri, F., Kotilainen, N., Vapa, M. (2007). An Adaptive Global-Local Memetic Algorithm to Discover Resources in P2P Networks. In: Giacobini, M. (eds) Applications of Evolutionary Computing. EvoWorkshops 2007. Lecture Notes in Computer Science, vol 4448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71805-5_7
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DOI: https://doi.org/10.1007/978-3-540-71805-5_7
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