Advertisement

Cluster Computing

, Volume 22, Issue 3, pp 705–720 | Cite as

Dynamic metric OSPF-based routing protocol for Software Defined Networks

  • Albert RegoEmail author
  • Sandra Sendra
  • Jose M. Jimenez
  • Jaime Lloret
Article
  • 76 Downloads

Abstract

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.

Keywords

Routing OSPF SDN Dynamic metric Multimedia 

Notes

Acknowledgements

This work has been partially supported by the “Ministerio de Educación, Cultura y Deporte”, through the “Ayudas para contratos predoctorales de Formación del Profesorado Universitario FPU (Convocatoria 2015)”. Grant No. FPU15/06837, by the “Ministerio de Economía y Competitividad”, through the “Convocatoria 2014. Proyectos I + D - Programa Estatal de Investigación Científica y Técnica de Excelencia” in the “Subprograma Estatal de Generación de Conocimiento”, project TIN2014-57991-C3-1-P, through the “Convocatoria 2016 - Proyectos I + D+I - Programa Estatal De Investigación, Desarrollo e Innovación 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 Investigación, Desarrollo e Innovación, convocatoria excelencia” (Project TIN2017-84802-C2-1-P).

References

  1. 1.
    Coltun, R., Ferguson, D., Moy, J.: OSPF for IPv6, RFC 5340.  https://doi.org/10.17487/rfc5340, July 2008. https://rfc-editor.org/rfc/rfc5340.txt
  2. 2.
    Software-Defined Networking (SDN) Definition. https://www.opennetworking.org/sdn-definition/. Accessed 15 Dec 2017
  3. 3.
    Jimenez, 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.v7i4.8794 CrossRefGoogle Scholar
  4. 4.
    Egea, 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.2017.2787959 CrossRefGoogle Scholar
  5. 5.
    Rego, 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.2017.7939153
  6. 6.
    Sendra, 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.v2i4.547 Google Scholar
  7. 7.
    Rakheja, 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/10.5120/7446-0401 Google Scholar
  8. 8.
    Sendra, 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.2017.7962735
  9. 9.
    Barbancho, 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_35
  10. 10.
    Barbancho, 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_58
  11. 11.
    Arabshahi, 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, 2001Google Scholar
  12. 12.
    Gunes, 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.2002.1039715
  13. 13.
    Ducatelle, 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-x CrossRefGoogle Scholar
  14. 14.
    Rajagopalan, 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.2006.02.006 CrossRefGoogle Scholar
  15. 15.
    RFC 3561 Ad hoc On-Demand Distance Vector (AODV) Routing, July 2003. https://www.rfc-editor.org/info/rfc3561. Accessed 08 may 2018
  16. 16.
    Zungeru, 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.2012.03.004 CrossRefGoogle Scholar
  17. 17.
    Karaboga, 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-z CrossRefGoogle Scholar
  18. 18.
    Ginsberg, 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.txt
  19. 19.
    Rekhter, 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.txt
  20. 20.
    Caria, 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.2015.7140324
  21. 21.
    Rothenberg, 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/10.1145/2342441.2342445
  22. 22.
    Zhu, 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_77
  23. 23.
    Ye, 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.2003.1240645
  24. 24.
    O’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.2015.7163767
  25. 25.
    Şimşek, 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.v9i1-2.12410 Google Scholar
  26. 26.
    Sanchez-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.v8i2.9123 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Instituto de Investigación para la Gestion Integrada de zonas CosterasUniversitat Politècnica de ValènciaValènciaSpain
  2. 2.Department of Signal Theory, Telematics and Communications Department (TSTC)Universidad de GranadaGranadaSpain

Personalised recommendations