Dynamic Metric OSPF-Based Routing Protocol for Software Defined Networks

[EN] Routing protocols are needed in networking to find the optimal path to reach the destination. However, networks are changing both their use finality and their technology. Paradigms like Software Defined Networks (SDNs) introduce the possibility and the necessity to improve the routing protocols. In this paper, a modification of the Open Shortest Path First (OSPF) routing protocol is proposed in order to allow the protocol to change the metric calculation dynamically according to the network requirements. Experiments, which compare our proposal against the OSPF protocol, are performed in five different scenarios. In these scenarios, the performance of the multimedia traffic has been increased 33% in terms of bandwidth utilization, 80% of loss rate reduction and delay reduction on VoIP communications.This work has been partially supported by the "Ministerio de Educacion, Cultura y Deporte", through the "Ayudas para contratos predoctorales de Formacion del Profesorado Universitario FPU (Convocatoria 2015)". Grant No. FPU15/06837, by the "Ministerio de Economia y Competitividad", through the "Convocatoria 2014. Proyectos I+D - Programa Estatal de Investigacion Cientifica y Tecnica de Excelencia" in the "Subprograma Estatal de Generacion de Conocimiento", project TIN2014-57991-C3-1-P, through the "Convocatoria 2016 - Proyectos I+D+I - Programa Estatal De Investigacion, Desarrollo e Innovacion Orientada a los retos de la sociedad" (Project TEC2016-76795-C6-4-R) and through the "Convocatoria 2017 - Proyectos I+D+I - Programa Estatal de Investigacion, Desarrollo e Innovacion, convocatoria excelencia" (Project TIN2017-84802-C2-1-P).Rego Mañez, A.; Sendra, S.; Jimenez, JM.; Lloret, J. (2019). Dynamic Metric OSPF-Based Routing Protocol for Software Defined Networks. Cluster Computing. 22(3):705-720. https://doi.org/10.1007/s10586-018-2875-7S705720223Coltun, R., Ferguson, D., Moy, J.: OSPF for IPv6, RFC 5340. https://doi.org/10.17487/rfc5340 , July 2008. https://rfc-editor.org/rfc/rfc5340.txtSoftware-Defined Networking (SDN) Definition. https://www.opennetworking.org/sdn-definition/ . Accessed 15 Dec 2017Jimenez, J.M., Romero, O., Rego, A., Dilendra, A., Lloret, J.: Study of multimedia delivery over software defined networks. Netw. Protoc. Algorithms 7(4), 37–62 (2015). https://doi.org/10.5296/npa.v7i4.8794Egea, S., Rego, A., Carro, B., Sanchez-Esguevillas, A., Lloret, J.: Intelligent IoT traffic classification using novel search strategy for fast based-correlation feature selection in industrial environments. IEEE Internet Things J. 5(3), 1616–1624 (2018). https://doi.org/10.1109/JIOT.2017.2787959Rego, A., Sendra, S., Jimenez, J.M., Lloret J.: OSPF routing protocol performance in software defined networks. In: Fourth International Conference on Software Defined Systems (SDS 2017), 8–11 May 2017, Valencia, Spain, https://doi.org/10.1109/SDS.2017.7939153Sendra, S., Fernández, P.A., Quilez, M.A., Lloret, J.: Study and performance of interior gateway IP routing protocols. Netw. Protoc. Algorithms 2(4), 88–117 (2010). https://doi.org/10.5296/npa.v2i4.547Rakheja, P., Kaour, P., Gupta, A., Sharma, A.: Performance analysis of RIP, OSPF, IGRP and EIGRP routing protocols in a network. Int. J. Comput. Appl. 48(18), 6–11 (2012). https://doi.org/10.5120/7446-0401Sendra, S., Rego, A., Lloret, J., Jimenez, J.M., Romero, O.: Including artificial intelligence in a routing protocol using software defined networks. In: IEEE International Conference on Communications Workshops (ICC Workshops 2017), 21–25 May 2017, Paris, France. https://doi.org/10.1109/ICCW.2017.7962735Barbancho, J., León, C., Molina, J., Barbancho, A., SIR: a new wireless sensor network routing protocol based on artificial intelligence. In: Advanced Web and Network Technologies, and Applications. APWeb 2006. Lecture Notes in Computer Science (LNCS), vol. 3842, pp. 271–275. https://doi.org/10.1007/11610496_35Barbancho, J., León, C., Molina, F.J., Barbancho, A.: Using artificial intelligence in wireless sensor routing protocols. In: Knowledge-Based Intelligent Information and Engineering Systems. (KES 2006). Lecture Notes in Computer Science, vol. 4251, pp. 475–482. Springer, New York. https://doi.org/10.1007/11892960_58Arabshahi, P., Gary, A., Kassabalidis, I., Das, A., Narayanan, S., Sharkawi, M.E., Marks, R.J.: Adaptive routing in wireless communication networks using swarm intelligence. In: AIAA 19th Annual Satellite Communications System Conference, Toulouse, France, April 17, 2001Gunes, M., Sorges, U., Bouazizi I.: ARA-the ant-colony based routing algorithm for MANETs. In: International Conference on Parallel Processing Workshops, Vancouver, BC, Canada, 21–21 Aug 2002. https://doi.org/10.1109/ICPPW.2002.1039715Ducatelle, F., Di Caro, G.A., Gambardella, L.M.: Principles and applications of swarm intelligence for adaptive routing in telecommunications networks. Swarm Intell. 4(3), 173–198 (2010). https://doi.org/10.1007/s11721-010-0040-xRajagopalan, S., Shen, C.: ANSI: a swarm intelligence-based unicast routing protocol for hybrid ad hoc networks. J. Syst. Archit. 52(8–9), 485–504 (2006). https://doi.org/10.1016/j.sysarc.2006.02.006RFC 3561 Ad hoc On-Demand Distance Vector (AODV) Routing, July 2003. https://www.rfc-editor.org/info/rfc3561 . Accessed 08 may 2018Zungeru, A.M., Ang, L., Seng, K.P.: Classical and swarm intelligence based routing protocols for wireless sensor networks: a survey and comparison. J. Netw. Comput. Appl. 35(5), 1508–1536 (2012). https://doi.org/10.1016/j.jnca.2012.03.004Karaboga, D., Okdem, S., Ozturk, C.: Cluster based wireless sensor network routing using artificial bee colony algorithm. Wirel. Netw. 18(7), 847–860 (2012). https://doi.org/10.1007/s11276-012-0438-zGinsberg, L., Litkowski, S., Previdi, S.: IS-IS route preference for extended IP and IPv6 reachability, RFC 7775. https://doi.org/10.17487/rfc7775 , February 2016. https://www.rfc-editor.org/rfc/rfc7775.txtRekhter, Y., Li, T., Hares, S.: A border gateway protocol 4 (BGP-4), RFC 4271. https://doi.org/10.17487/rfc4271 . Jan 2006. https://rfc-editor.org/rfc/rfc4271.txtCaria, M., Das, T., Jukan, A.: Divide and conquer: partitioning OSPF networks with SDN. In: IFIP/IEEE International Symposium on Integrated Network Management (IM 2015), 11–15 May, Ottawa (ON), Canada, 2015. https://doi.org/10.1109/INM.2015.7140324Rothenberg, C.E., Nascimento, M.R., Salvador, M.R., Corrêa, C.N.A., Cunha de Lucena, S., Raszuk, R.: Revisiting routing control platforms with the eyes and muscles of software-defined networking. In: HotSDN ‘12 Proceedings of the first workshop on Hot topics in software defined networks, August 13–17 (2012), Helsinki (Finland), pp. 13–18. https://doi.org/10.1145/2342441.2342445Zhu, M., Cao, J., Pang, D., He, Z., Xu, M.: SDN-based routing for efficient message propagation in VANET, In: Wireless Algorithms, Systems, and Applications (WASA 2015), Lecture Notes in Computer Science, vol. 9204, pp. 788–797. https://doi.org/10.1007/978-3-319-21837-3_77Ye, T., Hema, T.K., Kalyanaraman, S., Vastola, K.S, Yadav S.: Minimizing packet loss by optimizing OSPF weights using online simulation. Modeling, Analysis and Simulation of Computer Telecommunications Systems, 2003. MASCOTS 2003. In: 11th IEEE/ACM International Symposium on, Orlando, FL, USA, 27 Oct 2003. https://doi.org/10.1109/MASCOT.2003.1240645O’Halloran, C.: Dynamic adaptation of OSPF interface metrics based on network load. In: 26th Irish Signals and Systems Conference (ISSC), Ireland, Jun 2015. https://doi.org/10.1109/ISSC.2015.7163767Şimşek, M., Doğan, N., Akcayol, M.A.: A new packet scheduling algorithm for real-time multimedia streaming. Netw. Protoc. Algorithms 9(1–2), 28–47 (2017). https://doi.org/10.5296/npa.v9i1-2.12410Sanchez-Iborra, R., Cano, M.D., Garcia-Haro, J.: Revisiting VoIP QoE assessment methods: are they suitable for VoLTE? Netw. Protoc. Algorithms 8(2), 39–57 (2016). https://doi.org/10.5296/npa.v8i2.912

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