Abstract
We consider the survivable network design problem for simultaneous unicast and anycast flow requests. In this problem, a network is modeled by a connected, weighted and undirected graph with link cost follows All Capacities Modular Cost (ACMC) model. Given a set of flow demand, this problem aims at finding a set of connection with minimized network cost to protect the network against any single failure. This problem is proved to be NP-hard. In this paper, we propose a new Genetic Algorithm for solving the ACMC Survivable Network Design Problem (A-SNDP). Extensive simulation results on Polska, Germany and Atlanta network instances show that the proposed algorithm is much more efficient than the Tabu Search and other baseline algorithms such as FBB1 and FBB2 in terms of minimizing the network cost.
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References
Gładysz J et al (2010) Tabu search algorithm for survivable network design problem with simultaneous unicast and anycast flows. Int J Electron Telecommun 56(1):41-48, Versita Publisher, Warsaw
Walkowiak K (2008) Optimization of unicast and anycast flows in connection-oriented networks. In: Gervas O (ed) Proceedings of computational science and its applications—ICCSA 2008, LNCS, vol 5072. Springer, Perugia, pp 797–807
Anycast vs Unicast. http://communitydns.eu/Anycast.pdf. Accessed 18 July 2012
Walkowiak K (2006) A new function for optimization of working paths in survivable MPLS networks. In: Proceedings of computer and information sciences—ISCIS 2006. Springer, Istanbul, pp 424–433
Grover W (2004) Mesh-based survivable networks: options and strategies for optical, MPLS SONET and ATM networking. Prentice Hall PTR, New Jersey
Sharma V, Hellstrand F (2003) Framework for MPLS-based recovery. RFC 3469
Gladysz J, Walkowiak K (2009) Optimization of survivable networks with simultaneous unicast and anycast flows. In: Proceedings of ICUMT. Poland, pp 1–6
Binh H et al (2012) Heuristic algorithms for solving survivable network design problem with simultaneous unicast and anycast flows. In: Proceedings of 8th international conference on intelligence on computing, ICIC 2012. Huangshang, China, pp 137–145
Nissen V, Gold S (2008) Survivable network design with an evolution strategy. In: Proceedings of success in evolutionary computation. Springer, Berlin, pp 263–283
Pioro M, Medhi D (2004) Routing, flow, and capacity design in communication and computer networks. Morgan Kaufmann Publishers, San Francisco
Battiti R, Brunato M, Mascia F (2008) Reactive search intelligent optimization. Springer, New York
Vasseur J, Pickavet M, Demeester P (2004) Network recovery: protection and restoration of optical, SONET-SDH IP and MPLS. Morgan Kaufmann, San Francisco
Kasprzak A (1989) Algorithms of flow, capacity and topology structure in computer networks. Monography, Wroclaw
Walkowiak K (2003) Anycast communication—a new approach to survivability of connection-oriented networks. In: Proceedings of communications in computer and information science. Springer, Berlin, pp 378–389
Johnson D, Deering S (1999) Reserved IPv6 subnet anycast addresses. RFC 2526
Michalewicz Z (1995) Genetic algorithms + data structures = evolution programs, 3rd edn. Springer
Acknowledgments
This work was supported the National Foundation for Science and Technology Development (Nafosted), Ministry of Science and Technology under the project named “Design and Routing for Optical Networks” grant number 102.01.13.09.
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Binh, H.T.T., Ngo, S.H., Nguyen, D.N. (2013). Genetic Algorithm for Solving Survivable Network Design with Simultaneous Unicast and Anycast Flows. In: Yin, Z., Pan, L., Fang, X. (eds) Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013. Advances in Intelligent Systems and Computing, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37502-6_144
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DOI: https://doi.org/10.1007/978-3-642-37502-6_144
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