Energy-Efficient Routing in SDN-Based Access Networks

  • Siwar Ben Hadj SaidEmail author
  • Alexandre Petrescu
Part of the Computer Communications and Networks book series (CCN)


Forecast studies indicate a dramatic growth of Internet traffic due to streaming media services such as IPTV and Video-on-Demand (VoD). For these services, the bandwidth offered by the network is of paramount importance. At the same time, network energy consumption becomes a parameter that should be considered while designing new network architectures or new network mechanisms. For instance, in 5G networks, energy efficiency is considered as one of the key performance indicators. Therefore, in future access networks, one of the main challenges is reducing the power consumption in networks, while preserving the quality of service (QoS) perceived by the end user. A new energy-efficient routing algorithm is suggested, called GoGreen routing. This algorithm computes and selects, for each user traffic, the routing path that ensures less power consumption in the network and, at the same time, offers the adequate bandwidth. It uses a k-shortest path algorithm and considers two metrics, namely link power consumption and available bandwidth metrics. As the SDN controller is designed to have a global view of network topology including network interfaces properties of each node in the network, we suggest to implement the GoGreen routing as a module in the SDN controller.



This research was partially supported by the European Celtic-Plus project CONVINcE and it was partially funded by Finland, France, Sweden, and Turkey.


  1. 1.
    Ericsson White Paper (2015) 5G Energy PerformanceGoogle Scholar
  2. 2.
    Jaber M, Imran MA, Tafazolli R, Tukmanov A (2016) 5G backhaul challenges and emerging research directions: A survey. IEEE Access 4:1743–1766CrossRefGoogle Scholar
  3. 3.
    Bolla R, Bruschi R, Davoli F, Cucchietti F (2011) Energy efficiency in the future internet: a survey of existing approaches and trends in energy-aware fixed network infrastructures. IEEE Commun Surv Tutor 13(2):223–244CrossRefGoogle Scholar
  4. 4.
    Cisco White Paper (2015) Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 20152020Google Scholar
  5. 5.
    Soldani D, Manzalini A (2015) Horizon 2020 and beyond: on the 5G operating system for a true digital society. IEEE Veh Technol Mag 10(1):32–42CrossRefGoogle Scholar
  6. 6.
    European Commission (2013) Code of Conduct on Energy Consumption of Broadband Equipment, Version 5.0Google Scholar
  7. 7.
    Open Networking Foundation (ONF) (2012) Software-defined networking: the new norm for networks. Technical reportGoogle Scholar
  8. 8.
    Chiaraviglio L, Mellia M, Neri F (2009) Energy-aware backbone networks: a case study. In: IEEE international conference on communications workshops (ICC Workshops 2009). pp 1–5Google Scholar
  9. 9.
    Cianfrani A, Eramo V, Listanti M, Marazza M, Vittorini E (2010) An energy saving routing algorithm for a green OSPF protocol. In: INFOCOM IEEE conference on computer communications workshops 2010. IEEE, 2010, pp 1–5Google Scholar
  10. 10.
    Bianzino AP, Chiaraviglio L, Mellia M, Rougier J-L (2012) Grida: green distributed algorithm for energy-efficient IP backbone networks. Comput Netw 56(14):3219–3232CrossRefGoogle Scholar
  11. 11.
    Amokrane A, Langar R, Boutaba R, Pujolle G (2015) Flow-based management for energy efficient campus networks. IEEE Trans Netw Serv Manage 12(4):565–579CrossRefGoogle Scholar
  12. 12.
    Tadesse SS, Casetti C, Chiasserini C (2016) Energy-efficient traffic allocation in SDN-based backhaul networks: theory and implementation. CoRR. Accessed
  13. 13.
    Serafini P (1987) Some considerations about computational complexity for multi objective combinatorial problems. In: Recent advances and historical development of vector optimization. Springer, Berlin, pp 222–232Google Scholar
  14. 14.
    Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1(1):269–271MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Moy J (1998) RFC 2328: OSPF version 2. Technical reportGoogle Scholar
  16. 16.
    Eppstein D (1998) Finding the k shortest paths. SIAM J Comput 28(2):652–673MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Hoffman W, Pavley R (1959) A method for the solution of the n th best path problem. J. ACM (JACM) 6(4):506–514MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Katoh N, Ibaraki T, Mine H (1982) An efficient algorithm for k shortest simple paths. Networks 12(4):411–427MathSciNetCrossRefzbMATHGoogle Scholar
  19. 19.
    Yen JY (1971) Finding the k shortest loopless paths in a network. Manage Sci 17(11):712–716MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Lawler EL (1972) A procedure for computing the k best solutions to discrete optimization problems and its application to the shortest path problem. Manage Sci 18(7):401–405MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Lisa P (2012) WLAN design for optimized Wi-Fi video delivery,

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.CEA ListCEA SaclayGif-sur-Yvette, Ile-de-FranceFrance

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