Abstract
In this paper, a new algorithm for the solution of the Multicast Routing Problem based on Particle Swarm Optimization algorithm is presented and analyzed. A review of the most important evolutionary optimization algorithms for the solution of this problem is also given. Three different versions of the proposed algorithm are given and their quality is evaluated with experiments conducted on suitably modified benchmark instances of the Euclidean Traveling Salesman Problem from the TSP library. The results indicated the efficiency of the proposed method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aarts, E.H.L., Verhoeven, M.G.A.: Genetic local search for the traveling salesman problem. In [3], chapter G9.5, G9.5:1–G9.5:7
Arabshahi, P., Gray, A., Kassabalidis, I., Das, A.: Adaptive routing in wireless communication networks using swarm intelligence. In: Proceedings of the 19th AIAA Int. Commun. Satellite Syst. Conf. (2001)
Bäck, T., Fogel, D.B., Michalewicz, Z. (Eds.): Handbook of Evolutionary Computation. Oxford University Press, Oxford (1997)
Banks, A., Vincent, J., Anyakoha, C.: A review of particle swarm optimization. Part I: background and development. Nat. Comput. 6(4), 467–484 (2007)
Banks, A., Vincent, J., Anyakoha, C.: A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications. Nat. Comput. 7, 109–124 (2008)
Baras, J.S., Mehta, H.: A probabilistic emergent routing algorithm for mobile ad hoc networks. In: WiOpt’03: Modeling and Optimization in Mobile, AdHoc and Wireless Networks, Sophia-Antipoli, France, INRIA, March 3–5 2003
Cauvery, N.K., Viswanatha, K.V.: Routing in dynamic network using ants and genetic algorithm. Int. J. Comput. Sci. Network Secur. 9(3), 194–200 (2009)
Chow, C.H.: On multicast path finding algorithms. In: IEEE INFOCOM’91, pp. 1974–1283. IEEE, San Francisco (1991)
Clerc, M.: Particle Swarm Optimization. ISTE, London (2006)
Clerc, M., Kennedy, J.: The particle swarm: explosion, stability and convergence in a multi-dimensional complex space. IEEE Trans. Evol. Comput. 6, 58–73 (2002)
Crichigno, J., Baran, B.: Multiobjective multicast routing algorithm for traffic engineering. In: Proceedings of the 13th International Conference on Computer Communication Networks, CCCN 2004, pp. 301–306. IEEE, San Francisco (2004)
Crichigno, J., Baran, B.: Multiobjective multicast routing algorithm. In: Lorenz, P., de Souza, J.N., Dini, P. (eds.), Telecommunications and Networking - ICT 2004. 11th International Conference on Telecommunications, Fortaleza, Brazil, August 1–6, 2004. Proceedings, vol. 3124 of Lecture Notes in Computer Science, pp. 1029–1034. Springer, New York (2004)
Curran, E.: Swarm: Cooperative reinforcement learning for routing in ad-hoc networks. Master’s thesis, University of Dublin, Trinity College, September (2003)
Di Caro, G.: Ant colony optimization and its application to adaptive routing in telecommunication networks. PhD thesis, Université Libre de Bruxelles, Faculté des Sciences Appliquées, September (2004)
Di Caro, G., Dorigo, M.: Antnet: Distributed stigmergetic control for communication networks. J. Artif. Intell. Res. 9, 317–365 (1998)
Di Caro, G., Dorigo, M.: Two ant colony algorithms for best-effort routing in datagram network. In: Proceedings of the 10th IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS), (1998)
Di Caro, G., Dorigo, M.: Ant colonies for adaptive routing in packet-switched communications networks. In Eiben, A.E., Bäck, Th., Schoenauer, M., Schwefel, H.-P. (eds.), Parallel Problem Solving from Nature. PPSN V, vol. 1498 of Lecture Notes in Computer Science, pp. 673–682. Springer, New York (1998)
Di Caro, G.A., Ducatelle, F., Gambardella, L.M.: Theory and practice of ant colony optimization for routing in dynamic telecommunications networks. In: Sala, N., Orsucci, F. (eds.), Reflecting Interfaces: The Complex Coevolution of Information Technology Ecosystems, pp. 185–216. Idea Group, Hershey (2008)
Doar, M., Leslie, I.: How bad is naive multicast routing. In: INFOCOM’93. Proceedings. Twelfth Annual Joint Conference of the IEEE Computer and Communications Societies. Networking: Foundation for the Future, pp. 82–89. IEEE, San Francisco (1993)
Ducatelle, F., Di Caro, G., Gambarella, L.M.: Principles and applications of swarm intelligence for adaptive routing in telecommunications networks. Swarm Intell. 4(3), 173–198 (2010)
Engelbrecht, A.P.: Computational Intelligence: An Introduction, 2nd edn. Wiley, Chichester (2007)
Fabregat, R., Donoso, Y., Solano, F., Marzo, J.L.: Multitree routing for multicast flows: A genetic algorithm approach. In: Vitriá, J., Radeva, P., Aguiló, I. (eds.), Recent Advances in Artificial Intelligence Research and Development, pp. 399–405. IOS Press, Amsterdam (2004)
Farooq, M., Di Caro, G.: Routing protocols for next generation networks inspired by collective behaviors of insect societies: An overview. In: Blum, C., Merkle, D. (eds.), Swarm Intelligence: Introduction and Applications, pp. 101–160. Springer, New York (2008)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman and Company, New York (1979)
Hansen, P., Mladenović, N.: Variable neighborhood search: Principles and applications. Eur. J. Oper. Res. 130, 449–467 (2001)
Hansen, P., Mladenović, N., Moreno-Pérez, J.A.: Variable neighbourhood search: methods and applications. Ann. Oper. Res. 175, 367–407 (2010)
Hwang, R.-H., Do, W.-Y., Yang, S.-C.: Multicast routing based on genetic algorithms. In: WiOpt’03: Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks. INRIA Sophia-Antipolis, France, March 3–5, 2003
Ibaraki, T.: Combination with local search. In: [3], chapter G3.2, D3.2:1–D3.2:5
Ibaraki, T.: Simulated annealing and tabu search. In: [3], chapter D3.5, D3.5:1–D3.5:2
Kassabalidis, I., El-Sharkawi, M.A., Marks II, R.J., Arabshahi, P., Gray, A.A.: Swarm intelligence for routing in communication networks. In: Proceedings of the IEEE Globecom 2001, San Antonio, Texas (2001).
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of 1995 IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995)
Kennedy, J., Eberhart, R.: A discrete binary version of the particle swarm algorithm, In: Proceedings of 1997 IEEE International Conference on Systems, Man, and Cybernetics, vol. 5, pp. 4104–4108 (1997)
Kompleea, V.P., Pasquale, J.C., Polyzos, G.C.: Multicast routing for multimedia communication. IEEE/ACM Trans. Network. 1(3), 286–292 (1993)
Mukherjee, D., Acharyya, S.: Ant colony optimization techniques applied in network routing problem. Int. J. Comput. Appl. 1(15), 66–73 (2010)
Munetomo, M.: The genetic adaptive routing algorithm. In: Corne, D.W., Oates, M.J., Smith, G.D. (eds.), Telecommunications Optimization: Heuristic and Adaptive Techniques, pp. 151–166. Wiley, Chichester (2000)
Oh, J., Pyo, I., Pedram, M.: Constructing minimal spanning/steiner trees with bounded path length. In: European Design and Test Conference, pp. 244–249 (1996)
Oliveira, C.A.S., Pardalos, P.M.: A survey of combinatorial optimization problems in multicast routing. Comput. Oper. Res. 32(8), 1953–1981 (2005)
Oliveira, C.A.S., Pardalos, P.M., Resende, M.G.C.: Optimization problems in multicast tree construction. In: [43], 701–731
Pinto, D., Barán, B.: Multiobjective multicast routing with ant colony optimization. In: Gaiti, D. (ed.), Network Control and Engineering for QoS, Security and Mobility V, vol. 213 of IFIP International Federation of Information Processing, pp. 101–115. Springer, New York (2006)
Pinto, D., Barán, B., Fabregat, R.: Multi-objective multicast routing based on ant colony optimization. In: López, B., Meléndez, J., Radeva, P., Vitriá, J. (eds), Artificial Intelligence Research and Development, pp. 363–370. IOS Press, Amsterdam (2005)
Poli, R., Kennedy, J., Blackwell, T.: Particle swarm optimization. an overview. Swarm Intell. 1, 33–57 (2007)
Purkayastha, P.: Multipath routing algorithms for communication networks: ant routing and optimization based approaches. PhD thesis, Department of Electrical and Computer Engineering, University of Meryland (2009)
Resende, M.G.C., Pardalos, P.M. (eds.): Handbook of Optimization in Telecommunications. Springer, New York (2006)
Saleem, M., Di Caro, G.A., Farooq, M.: Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions. Inform. Sci. 181, 4597–4624 (2011)
Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: Proceedings of 1998 IEEE World Congress on Computational Intelligence, pp. 69–73 (1998)
Sigel, E., Denby, B., Le Hégarat-Mascle, S.: Application of ant colony optimization to adaptive routing in a leo telecommunications satellite network. Annales des Télecommunications 57(5–6), 520–539 (2002)
Takahashi, H., Mutsuyama, A.: An approximate solution for the steiner problem in graphs. Mathematica Japonica 6, 573–577 (1980)
Tode, H., Sakai, Y., Yamamoto, M., Okada, H., Tezuka, Y.: Multicast routing algorithm for nodal load balancing. In: IEEE INFOCOM’92, pp. 2086–2095. IEEE, San Francisco (1992)
Waxman, B.M.: Routing of multipoint connections. IEEE J. Sel. Area Comm. 1(3), 286–292 (1988)
Wu, J.J., Hwang, R.-H.: Multicast routing with multiple constraints. Inform. Sci. 124, 29–57 (2000)
Xu, Y., Qu, R., Li, R.: A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems. Ann. Oper. Res. 1–29 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Marinakis, Y., Migdalas, A. (2014). A Particle Swarm Optimization Algorithm for the Multicast Routing Problem. In: Batsyn, M., Kalyagin, V., Pardalos, P. (eds) Models, Algorithms and Technologies for Network Analysis. Springer Proceedings in Mathematics & Statistics, vol 104. Springer, Cham. https://doi.org/10.1007/978-3-319-09758-9_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-09758-9_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09757-2
Online ISBN: 978-3-319-09758-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)