Abstract
Peer-to-peer (P2P) topology has a significant influence on the performance, search efficiency and functionality, and scalability of the application. In this paper, we investigate a multi-swarm approach to the problem of neighbor selection (NS) in P2P networks. Particle swarm share some common characteristics with P2P in the dynamic socially environment. Each particle encodes the upper half of the peer-connection matrix through the undirected graph, which reduces the search space dimension. The portion of the adjustment to the velocity influenced by the individual’s cognition, the group cognition from multi-swarms, and the social cognition from the whole swarm, makes an important influence on the particles’ ergodic and synergetic performance. We also attempt to theoretically prove that the multi-swarm optimization algorithm converges with a probability of 1 towards the global optima. The performance of our approach is evaluated and compared with other two different algorithms. The results indicate that it usually required shorter time to obtain better results than the other considered methods, specially for large scale problems.
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Lua, E. K., Crowcroft, J., Pias, M., Sharma, R., & Lim, S. (2005). A survey and comparison of peer-to-peer overlay network schemes. IEEE Communications Surveys and Tutorials, 7(2), 72–93.
Kwok, S. (2006). P2P searching trends: 2002–2004. Information Processing and Management, 42, 237–247.
Huang, X., Chang, C., & Chen, M. (2006). PeerCluster: a cluster-based peer-to-peer system. IEEE Transactions on Parallel and Distributed Systems, 17(10), 1110–1123.
Belmonte, M. V., Conejo, R., Díaz, M., & Pérez-de-la-Cruz, J. L. (2005). Lecture notes in artificial intelligence : Vol. 4177. Coalition formation in P2P file sharing systems (pp. 153–162). CAEPIA’05. Berlin: Springer.
Idris, T., & Altmann, J. (2006). A market-managed topology formation algorithm for peer-to-peer file sharing networks. Lecture Notes in Computer Science, 4033, 61–77.
Cho, H. (2007). Lecture notes in computer science : Vol. 4490. An update propagation algorithm for P2P file sharing over wireless mobile networks (pp. 753–760). ICCS’07. Berlin: Springer.
Pianese, F., Perino, D., Keller, J., & Biersack, E. W. (2007). PULSE: an adaptive, incentive-based, unstructured P2P live streaming system. IEEE Transactions on Multimedia, 9(8), 1645–1660.
Sigurdsson, H. M., Halldorsson, U. R., & Hasslinger, G. (2007). Potentials and challenges of peer-to-peer based content distribution. Telematics and Informatics, 24, 348–365.
Yang, S., & Chen, I. (2008). A social network-based system for supporting interactive collaboration in knowledge sharing over peer-to-peer network. International Journal of Human-Computer Studies, 66, 36–50.
Kim, J. K., Kim, H. K., & Cho, Y. H. (2008). A user-oriented contents recommendation system in peer-to-peer architecture. Expert Systems with Applications, 34, 300–312.
Sen, S., & Wang, J. (2004). Analyzing peer-to-peer traffic across large networks. IEEE/ACM Transactions on Networking, 12(2), 219–232.
Leung, A., & Kwok, Y. (2005). Lecture notes in computer science : Vol. 3794. An efficient and practical greedy algorithm for server-peer selection in wireless peer-to-peer file sharing networks (pp. 1016–1025). MSN’05. Berlin: Springer.
Ardizzone, E., Gatani, L., LaCascia, M., LoRe, G., & Ortolani, M. (2007). Enhanced P2P services providing multimedia content. Advances in Multimedia, 2007(2), 1–12.
Androutsellis-theotokis, S., & Spinellis, D. (2004). A survey of peer-to-peer content distribution technologies. ACM Computing Surveys, 36(4), 335–371.
Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: from natural to artificial systems. New York: Oxford University Press.
Clerc, M. (2006). Particle swarm optimization. London: ISTE.
Abraham, A., Guo, H., & Liu, H. (2006). Swarm intelligence: foundations, perspectives and applications. In Swarm Intelligent Systems, Studies in Computational Intelligence (pp. 3–25). Berlin: Springer.
Schollmeier, R. (2001). A definition of peer-to-peer networking for the classification of peer-to-peer architectures and applications. In Proceedings of the 1st international August conference on peer-to-peer computing (pp. 101–102).
Ghosal, D., Poon, B. K., & Kong, K. (2005). P2P contracts: a framework for resource and service exchange. Future Generation Computer Systems, 21, 333–347.
Koo, S. G., Kannan, K., & Lee, C. S. (2006). A genetic-algorithm-based neighbor-selection strategy for hybrid peer-to-peer networks. Future Generation Computer Systems, 22, 732–741.
Surana, S., Godfrey, B., Lakshminarayanan, K., Karp, R., & Stoica, I. (2006). Load balancing in dynamic structured peer-to-peer systems. Performance Evaluation, 63, 217–240.
Merrer, E., Kermarrec, A., & Massoulié, L. (2006). Peer-to-peer size estimation in large and dynamic networks: a comparative study. In Proceedings of 15th IEEE international symposium on high performance distributed computing (pp. 7–17).
Meo, M., & Milan, F. (2008). QoS content management for P2P file-sharing applications. Future Generation Computer Systems, 24, 213–221.
Risson, J., & Moors, T. (2006). Survey of research towards robust peer-to-peer networks: search methods. Computer Networks, 50, 3485–3521.
Habib, A., & Chuang, J. (2006). Service differentiated peer selection: an incentive mechanism for peer-to-peer media streaming. IEEE Transactions on Multimedia, 8(3), 610–623.
Lo, V., Zhou, D., Liu, Y., GauthierDickey, C. S., & Li, J. (2005). Scalable supernode selection in peer-to-peer overlay networks. In Proceedings of the 2nd IEEE international workshop on hot topics in peer-to-peer systems (pp. 18–27).
Kothapalli, K., & Scheideler, C. (2005). Supervised peer-to-peer systems. In Proceedings of the 8th international symposium on parallel architectures, Algorithms and Networks (pp. 188–193).
Koulouris, T., Henjes, R., Tutschku, K., & de Meer, H. (2004). Implementation of adaptive control for P2P overlays. Lecture Notes in Computer Science, 2982, 292–306.
Liu, Y., Xiao, L., Esfahanian, A., & Ni, L. M. (2005). Approaching optimal peer-to-peer overlays. In Proceedings of the 13th IEEE international symposium on modeling, analysis, and simulation of computer and telecommunication systems (pp. 407–414).
Leung, A. K., & Kwok, Y. (2008). On localized application-driven topology control for energy-efficient wireless peer-to-peer file sharing. IEEE Transactions on Mobile Computing, 7(1), 66–80.
Mastronarde, N., Turaga, D. S., & van der Schaar, M. (2007). Collaborative resource exchanges for peer-to-peer video streaming over wireless mesh networks. IEEE Journal on Selected Areas in Communications, 25(1), 108–118.
Fenner, T., Levene, M., Loizou, G., & Roussos, G. (2007). A stochastic evolutionary growth model for social networks. Computer Networks, 51, 4586–4595.
Sacha, J., Dowling, J., Cunningham, R., & Meier, R. (2006). Discovery of stable peers in a self-organising peer-to-peer gradient topology. Lecture Notes in Computer Science, 4025, 70–83.
Bisnik, N., & Abouzeid, A. A. (2007). Optimizing random walk search algorithms in P2P networks. Computer Networks, 51(6), 1499–1514.
Kersch, P., Szabo, R., Cheng, L., Jean, K., & Galis, A. (2007). Stochastic maintenance of overlays in structured P2P systems. Computer Communications. doi:10.1016/j.comcom.2007.08.017.
Krishnamurthy, B., & Wang, J. (2001). Topology modeling via cluster graphs. In Proceedings of the 1st ACM SIGCOMM workshop on Internet measurement (pp. 19–23).
Padmanabhan, V. N., & Subramanian, L. (2001). An investigation of geographic mapping techniques for Internet hosts. In Proceedings of the ACM conference on applications, technologies, architectures, and protocols for computer communications (pp. 173–185).
Nakao, A., Peterson, L., & Bavier, A. (2003). A routing underlay for overlay networks. In Proceedings of the ACM conference on applications, technologies, architectures, and protocols for computer communications (pp. 11–18).
Xu, X. (2005). ABC: a cluster-based protocol for resource location in peer-to-peer systems. Journal of Parallel and Distributed Computing. doi:10.1016/j.jpdc.2005.02.004.
Ramaswamy, L., Gedik, B., & Liu, L. (2005). A distributed approach to node clustering in decentralized peer-to-peer networks. IEEE Transactions on Parallel and Distributed Systems, 16(9), 814–829.
Tewari, S., & Kleinrock, L. (2007). Optimal search performance in unstructured peer-to-peer networks with clustered demands. IEEE Journal on Selected Areas in Communications, 25(1), 84–95.
Kurmanowytsch, R., Kirda, E., Kerer, C., & Dustdar, S. (2003). OMNIX: a topology-independent P2P middleware. In Proceedings of the 15th conference on advanced information systems engineering.
Gupta, R., Sekhri, V., & Somani, A. K. (2006). CompuP2P: an architecture for Internet computing using peer-to-peer networks. IEEE Transactions on Parallel and Distributed Systems, 17(11), 1306–1320.
Zeinalipour-Yazti, D., Kalogeraki, V., & Gunopulos, D. (2007). pFusion: a P2P architecture for Internet-scale content-based search and retrieval. IEEE Transactions on Parallel and Distributed Systems, 18(6), 804–817.
Ghanea-Hercock, R. A., Wang, F., & Sun, Y. (2006). Self-organizing and adaptive peer-to-peer network. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 36(6), 1230–1236.
Biersack, E. W., Rodriguez, P., & Felber, P. (2004). Lecture notes in computer science : Vol. 3266. Performance analysis of peer-to-peer networks for file distribution (pp. 1–10). QofIS’04. Berlin: Springer.
Carchiolo, V., Malgeri, M., Mangioni, G., & Nicosia, V. (2007). Emerging structures of P2P networks induced by social relationships. doi:10.1016/j.comcom.2007.08.016.
Zhuge, H., & Li, X. (2007). Peer-to-peer in metric space and semantic space. IEEE Transactions on Knowledge and Data Engineering, 19(6), 759–771.
Wang, S., Chou, H., Wei, D., & Kuo, S. (2007). On the fundamental performance limits of peer-to-peer data replication in wireless Ad hoc networks. Journal on Selected Areas in Communications, 25(1), 211–221.
Qiu, D., & Sang, W. (2007). Global stability of peer-to-peer file sharing systems. Computer Communications. doi:10.1016/j.comcom.2007.08.012.
Salman, A., Ahmad, I., & Al-Madani, S. (2002). Particle swarm optimization for task assignment problem. Microprocessors and Microsystems, 26, 363–371.
Clerc, M., & Kennedy, J. (2002). The particle swarm—explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation, 6(1), 58–73.
Cristian, T. I. (2003). The particle swarm optimization algorithm: convergence analysis and parameter selection. Information Processing Letters, 85(6), 317–325.
van den Bergh, F., & Engelbrecht, A. P. (2006). A study of particle swarm optimization particle trajectories. Information Sciences, 176, 937–971.
Liu, H., Abraham, A., & Clerc, M. (2007). Chaotic dynamic characteristics in swarm intelligence. Applied Soft Computing, 7, 1019–1026.
Kennedy, J., & Eberhart, R. (2001). Swarm Intelligence. Los Altos: Kaufmann.
Liu, H., Li, B., Ji, Y., & Sun, T. (2006). Particle swarm optimisation from lbest to gbest. In Applied soft computing technologies: the challenge of complexity (pp. 537–545). Berlin: Springer.
Grosan, C., Abraham, A., & Nicoara, M. (2005). Search optimization using hybrid particle sub-swarms and evolutionary algorithms. International Journal of Simulation Systems, Science and Technology, 6(10), 60–79.
Jiang, C. W., & Etorre, B. (2005). A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimisation. Mathematics and Computers in Simulation, 68, 57–65.
Liu, H., & Abraham, A. (2007). An hybrid fuzzy variable neighborhood particle swarm optimization algorithm for solving quadratic assignment problems. Journal of Universal Computer Science, 13(7), 1032–1054.
Liang, J. J., Qin, A. K., Suganthan, P. N., & Baskar, S. (2006). Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Transactions on Evolutionary Computation, 10(3), 281–295.
Elshamy, W., Emara, H. M., & Bahgat, A. (2007). Clubs-based particle swarm optimization. In Proceedings of the IEEE international conference on swarm intelligence symposium (Vol. 1, pp. 289–296).
Guo, C., & Tang, H. (2001). Global convergence properties of evolution strategies. Mathematica Numerica Sinica, 23(1), 105–110.
He, R., Wang, Y., Wang, Q., Zhou, J., & Hu, C. (2005). An improved particle swarm optimization based on self-adaptive escape velocity. Journal of Software, 16(12), 2036–2044.
Halmos, P. (1950). Measure theory. New York: Van Nostrand.
Xu, Z., Cheng, G., & Liang, Y. (1999). Search capability for an algebraic crossover. Journal of Xi’an Jiaotong University, 33(10), 88–99.
Whitley, L. D. (1991). Fundamental principles of deception in genetic search. In Foundation of genetic algorithms (pp. 221–241). California: Kaufmann.
Mastrolilli, M., & Gambardella, L. M. (2002). Effective neighborhood functions for the flexible job shop problem. Journal of Scheduling, 3(1), 3–20.
Holland, J. H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Reading: Addison-Wesley.
Abraham, A. (2005). Evolutionary computation. In Handbook for measurement systems design (pp. 920–931). London: Wiley.
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This work is supported partially by NSFC Grant 60873054.
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Abraham, A., Liu, H. & Hassanien, A.E. Multi swarms for neighbor selection in peer-to-peer overlay networks. Telecommun Syst 46, 195–208 (2011). https://doi.org/10.1007/s11235-010-9285-3
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DOI: https://doi.org/10.1007/s11235-010-9285-3