Photonic Network Communications

, Volume 37, Issue 1, pp 24–37 | Cite as

A control and management architecture supporting autonomic NFV services

  • Luis VelascoEmail author
  • Ramon Casellas
  • Sergio Llana
  • Lluís Gifre
  • Ricardo Martínez
  • Ricard Vilalta
  • Raúl Muñoz
  • Marc Ruiz
Original Paper


The proposed control, orchestration and management (COM) architecture is presented from a high-level point of view; it enables the dynamic provisioning of services such as network data connectivity or generic network slicing instances based on virtual network functions (VNF). The COM is based on Software Defined Networking (SDN) principles and is hierarchical, with a dedicated controller per technology domain. Along with the SDN control plane for the provisioning of connectivity, an ETSI NFV management and orchestration system is responsible for the instantiation of Network Services, understood in this context as interconnected VNFs. A key, novel component of the COM architecture is the monitoring and data analytics (MDA) system, able to collect monitoring data from the network, datacenters and applications which outputs can be used to proactively reconfigure resources thus adapting to future conditions, like load or degradations. To illustrate the COM architecture, a use case of a Content Delivery Network service taking advantage of the MDA ability to collect and deliver monitoring data is experimentally demonstrated.


Control Orchestration and management Disaggregated optical networks Autonomic networking 



The research leading to these results has received funding from the European Community’s through the Metro-Haul project (G.A. No. 761727), from the AEI/FEDER TWINS project (TEC2017-90097-R), from the MINECO project DESTELLO (TEC2015-69256-R) and from the Catalan Institution for Research and Advanced Studies (ICREA).


  1. 1.
    Casellas, R., et al.: Control, management and orchestration of optical networks: evolution, trends and challenges. IEEE/OSA J. Lightw. Technol. 36, 1–13 (2018)CrossRefGoogle Scholar
  2. 2.
    METRO High bandwidth, 5G Application-aware optical network, with edge storage, compute and low latency (Metro-Haul). (On-line). Accessed Oct 2018
  3. 3.
    Velasco, L., et al.: A service-oriented hybrid access network and cloud architecture. IEEE Commun. Mag. 53, 159–165 (2015)CrossRefGoogle Scholar
  4. 4.
    Behringer, M., Pritikin, M., Bjarnason, S., Clemm, A., Carpenter, B., Jiang, S., Ciavaglia, L.: Autonomic networking: definitions and design goals. In: IETF RFC 7575 (2015)Google Scholar
  5. 5.
    Rafique, D., Velasco, L.: Machine learning for optical network automation: overview, architecture and applications (Invited Tutorial). IEEE/OSA J. Opt. Commun. Netw. (JOCN) 10, D126–D143 (2018)CrossRefGoogle Scholar
  6. 6.
    Vela, A.P., et al.: BER degradation detection and failure identification in elastic optical networks. IEEE/OSA J. Lightw. Technol. (JLT) 35, 4595–4604 (2017)CrossRefGoogle Scholar
  7. 7.
    Vela, A.P., et al.: Soft failure localization during commissioning testing and lightpath operation [Invited]. IEEE/OSA J. Opt. Commun. Netw. (JOCN) 10, A27–A36 (2018)CrossRefGoogle Scholar
  8. 8.
    Morales, F., et al.: Dynamic core VNT adaptability based on predictive metro-flow traffic models. IEEE/OSA J. Opt. Commun. Netw. (JOCN) 9, 1202–1211 (2017)CrossRefGoogle Scholar
  9. 9.
    Morales, F., et al.: Virtual network topology adaptability based on data analytics for traffic prediction (Invited). IEEE/OSA J. Opt. Commun. Netw. (JOCN) 9, A35–A45 (2017)CrossRefGoogle Scholar
  10. 10.
    de Miguel, I., et al.: Cognitive dynamic optical networks [invited]. IEEE/OSA J. Opt. Commun. Networking 5, A107–A118 (2013)CrossRefGoogle Scholar
  11. 11.
    Muñoz, R., et al.: Transport network orchestration for end-to-end multi-layer provisioning across heterogeneous SDN/OpenFlow and GMPLS/PCE Control domains. IEEE/OSA J. Lightw. Technol. 33, 1540–1548 (2015)CrossRefGoogle Scholar
  12. 12.
    Enns, R. et al.: Network configuration protocol (NETCONF). In: IETF RFC 6241 (2011)Google Scholar
  13. 13.
    Bjorklund, M.: YANG—a data modeling language for the network configuration protocol (NETCONF). In: IETF RFC 6020 (2010)Google Scholar
  14. 14.
    Leira, R., Aracil, J., López de Vergara, J., Roquero, P., González, I.: High-speed optical networks latency measurements in the microsecond timescale with software-based traffic injection. Elsevier Opt. Switch. Netw. 29, 39–45 (2018)CrossRefGoogle Scholar
  15. 15.
    Kamiyama, N., et al.: Optimally designing ISP-operated CDN. IEICE Trans. Commun. E96-B, 790–801 (2013)CrossRefGoogle Scholar
  16. 16.
    Spagna, S., et al.: Design principles of an operator-owned highly distributed content delivery network. IEEE Commun. Mag. 51, 132–140 (2013)CrossRefGoogle Scholar
  17. 17.
    Ruiz, M., et al.: Big data-backed video distribution in the telecom cloud. Elsevier Comput. Commun. 84, 1–11 (2016)CrossRefGoogle Scholar
  18. 18.
    ISO Standard: Dynamic adaptive streaming over HTTP (DASH)—part 1: media presentation description and segment formats. ISO/IEC 23009-1 (2014)Google Scholar
  19. 19.
    de Vleeschauwer, D., Robinson, D.C.: Optimum caching strategies for a telco CDN. Bell Labs Tech. J. 16, 115–132 (2011)CrossRefGoogle Scholar
  20. 20.
    Asensio, A. et al.: Scalability of telecom cloud architectures for live-TV distribution. In: Proceedings of OFC (2015)Google Scholar
  21. 21.
    Ruiz, M., Velasco, L.: Performance evaluation of light-tree schemes in flexgrid optical networks. IEEE Commun. Lett. 18, 1731–1734 (2014)CrossRefGoogle Scholar
  22. 22.
    Ruiz, M., Velasco, L.: Serving multicast requests on single layer and multilayer flexgrid networks. IEEE/OSA J. Opt. Commun. Netw. (JOCN) 7, 146–155 (2015)CrossRefGoogle Scholar
  23. 23.
    Vela, A.P., et al.: Distributing data analytics for efficient multiple traffic anomalies detection. Elsevier Comput. Commun. 107, 1–12 (2017)CrossRefGoogle Scholar
  24. 24.
    Gifre, L., et al.: Experimental assessment of ABNO-driven multicast connectivity in flexgrid networks [Invited]. IEEE/OSA J. Lightw. Technol. (JLT) 33, 1549–1556 (2015)CrossRefGoogle Scholar
  25. 25.
    Open Networking Foundation: Functional requirements for transport API. ONF TR-527 (2016)Google Scholar
  26. 26.
    Busi, I.: Transport northbound interface applicability statement and use cases. In: Draft IETF, Work-in-Progress October 2017Google Scholar
  27. 27.
    Velasco, L., et al.: An architecture to support autonomic slice networking [Invited]. IEEE/OSA J. Lightw. Technol. (JLT) 36, 135–141 (2018)CrossRefGoogle Scholar
  28. 28.
    Velasco, L., et al.: Building autonomic optical whitebox-based networks. IEEE/OSA J. Lightw. Technol. (JLT) 36, 3097–3104 (2018)CrossRefGoogle Scholar
  29. 29.
    Gifre, L., Izquierdo-Zaragoza, J.-L., Ruiz, M., Velasco, L.: Autonomic disaggregated multilayer networking. IEEE/OSA J. Opt. Commun. Netw. (JOCN) 10, 482–492 (2018)CrossRefGoogle Scholar
  30. 30.
    OpenStack Pike. (On-line). Accessed Oct 2018
  31. 31.
    Filebeat. (On-line). Accessed Oct 2018
  32. 32.
    Logstash. (On-line). Accessed Oct 2018
  33. 33.
    gRPC: A high performance, open-source universal RPC framework. (On-line). Accessed Oct 2018
  34. 34.
    Claise, B. et al.: Specification of the IP flow information export (IPFIX) protocol for the exchange of flow information. In: IETF RFC 7011 (2013)Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Optical Communications Group (GCO)Universitat Politècnica de Catalunya (UPC)BarcelonaSpain
  2. 2.Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)BarcelonaSpain
  3. 3.Universidad Autónoma de Madrid (UAM)MadridSpain

Personalised recommendations