Using the RFC 7575 and Models at Runtime for Enabling Autonomic Networking in SDN
Resumo
The programmable network architectures that emerged in the last decade have allowed new ways to enable Autonomic Networks. However, there are several open issues to address before making such a possibility into a feasible reality. For instance, defining network goals, translating them into network rules, and granting the correct functioning of the network control loop in a self-adaptive manner are examples of complex tasks required to enable an autonomic networking environment. Fortunately, architectures based on the concept of Models at Runtime (MART) provide ways to overcome such complexity. This paper proposes a MART-based framework – using the RFC 7575 as reference (i.e., definitions and design goals for autonomic networking) – to implement autonomic management into a programmable network. The evaluation shows the proposed framework is suitable for satisfying the functional and performance requirements of a simulated network.
Palavras-chave:
Autonomic Networking, SDN, Models at Runtime
Referências
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Behringer, M. H., Pritikin, M., Bjarnason, S., Clemm, A., Carpenter, B. E., Jiang, S., and Ciavaglia, L. (2015). Autonomic Networking: Definitions and Design Goals. RFC 7575.
Benayas, F., Carrera, Á ., García-Amado, M., and Iglesias, C. A. (2019). A semantic data lake framework for autonomous fault management in sdn environments. Transactions on Emerging Telecommunications Technologies, 30(9):e3629.
Bencomo, N. and Blair, G. (2009). Using architecture models to support the generation and operation of component-based adaptive systems. In Software engineering for self-adaptive systems, pages 183–200. Springer.
Blair, G., Bencomo, N., and France, R. B. (2009). Models@ run.time. Computer, 42(10):22–27.
Eckert, T., Behringer, M. H., and Bjarnason, S. (2020). An Autonomic Control Plane (ACP). Internet-Draft draft-ietf-anima-autonomic-control-plane-30, Internet Engineering Task Force. Work in Progress.
Gelenbe, E. (2013). A software defined self-aware network: The cognitive packet network. In 2013 Ninth International Conference on Semantics, Knowledge and Grids, pages 1–5.
Gronback, R. C. (2009). Eclipse modeling project: a domain-specific language (DSL) toolkit. Pearson Education.
Jiang, S., Carpenter, B. E., and Behringer, M. H. (2015). General Gap Analysis for Autonomic Networking. RFC 7576.
Kalmbach, P., Zerwas, J., Babarczi, P., Blenk, A., Kellerer, W., and Schmid, S. (2018). Empowering self-driving networks. In Proceedings of the AfternoonWorkshop on Self-Driving Networks, pages 8–14. ACM.
Kalnins, A., Vilitis, O., Celms, E., Kalnina, E., Sostaks, A., and Barzdins, J. (2007). Building tools by model transformations in eclipse. In Proceedings of DSM, volume 7, pages 194–207.
Koutsouris, N., Tsagkaris, K., Demestichas, P., Mamatas, L., Clayman, S., and Galis, A. (2013). Managing software-driven networks with a unified management framework. In 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013), pages 1084–1085.
Kreutz, D., Ramos, F. M., Verissimo, P. E., Rothenberg, C. E., Azodolmolky, S., and Uhlig, S. (2014). Software-defined networking: A comprehensive survey. Proceedings of the IEEE, 103(1):14–76.
Li, H., Que, X., Hu, Y., Xiangyang, G., and Wendong, W. (2013). An autonomic management architecture for sdn-based multi-service network. In 2013 IEEE Globecom Workshops (GC Wkshps), pages 830–835.
Lopes, F. A., Santos, M., Fidalgo, R., and Fernandes, S. (2015). Model-driven networking: A novel approach for sdn applications development. In 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), pages 770–773.
Mestres, A., Rodriguez-Natal, A., Carner, J., Barlet-Ros, P., Alarcón, E., Solé, M., Muntés-Mulero, V., Meyer, D., Barkai, S., Hibbett, M. J., et al. (2017). Knowledge-defined networking. ACM SIGCOMM Computer Communication Review, 47(3):2–10.
Movahedi, Z., Ayari, M., Langar, R., and Pujolle, G. (2012). A survey of autonomic network architectures and evaluation criteria. IEEE Communications Surveys & Tutorials, 14(2):464–490.
Ochoa-Aday, L., Cervelló-Pastor, C., and Fernández-Fernández, A. (2019). Self-healing and sdn: bridging the gap. Digital Communications and Networks.
Poulios, G., Tsagkaris, K., Demestichas, P., Tall, A., Altman, Z., and Destr´e, C. (2014). Autonomics and sdn for self-organizing networks. In 2014 11th International Symposium on Wireless Communications Systems (ISWCS), pages 830–835.
Puterman, M. L. (2014). Markov decision processes: discrete stochastic dynamic programming. John Wiley & Sons.
Qi, Q., Wang, W., Gong, X., and Que, X. (2014). A sdn-based network virtualization architecture with autonomie management. In 2014 IEEE Globecom Workshops (GC Wkshps), pages 178–182.
Samaan, N. and Karmouch, A. (2009). Towards autonomic network management: an analysis of current and future research directions. IEEE Communications Surveys & Tutorials, 11(3):22–36.
Schaller, S. and Hood, D. (2017). Software defined networking architecture standardization. Computer Standards & Interfaces, 54:197–202.
Stamou, A., Dimitriou, N., Kontovasilis, K., and Papavassiliou, S. (2019). Autonomic handover management for heterogeneous networks in a future internet context: A survey. IEEE Communications Surveys & Tutorials.
Tessler, C., Efroni, Y., and Mannor, S. (2019). Action robust reinforcement learning and applications in continuous control. In International Conference on Machine Learning, pages 6215–6224. PMLR.
Tsagkaris, K., Logothetis, M., Foteinos, V., Poulios, G., Michaloliakos, M., and Demestichas, P. (2015). Customizable autonomic network management: Integrating autonomic network management and software-defined networking. IEEE Vehicular Technology Magazine, 10(1):61–68.
Tuncer, D., Charalambides, M., Clayman, S., and Pavlou, G. (2015). Adaptive resource management and control in software defined networks. IEEE Transactions on Network and Service Management, 12(1):18–33.
Volpato, F., Silva, M. P. D., Gonçalves, A. L., and Dantas, M. A. R. (2017). An autonomic qoe-aware management architecture for software-defined networking. In 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pages 220–225.
Wickboldt, J. A., De Jesus, W. P., Isolani, P. H., Both, C. B., Rochol, J., and Granville, L. Z. (2015). Software-defined networking: management requirements and challenges. IEEE Communications Magazine, 53(1):278–285.
Yahia, I. G. B., Bendriss, J., Samba, A., and Dooze, P. (2017). Cognitive 5g networks: Comprehensive operator use cases with machine learning for management operations. In 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN), pages 252–259.
Zhou, T., Xiangyang, G., Hu, Y., Que, X., and Wendong, W. (2013). Pindswitch: A sdn-based protocol-independent autonomic flow processing platform. In 2013 IEEE Globecom Workshops (GC Wkshps), pages 842–847.
Aßmann, U., Gotz, S., Józéquel, J.-M., Morin, B., and Trapp, M. (2014). A reference architecture and roadmap for models@ run. time systems. In Models@ run. time, pages 1–18. Springer.
Ayoubi, S., Limam, N., Salahuddin, M. A., Shahriar, N., Boutaba, R., Estrada-Solano, F., and Caicedo, O. M. (2018). Machine learning for cognitive network management. IEEE Communications Magazine, 56(1):158–165.
Barron, J., Crotty, M., Elahi, E., Riggio, R., Lopez, D. R., and de Leon, M. P. (2016). Towards self-adaptive network management for a recursive network architecture. In Network Operations and Management Symposium (NOMS), 2016 IEEE/IFIP, pages 1143–1148. IEEE.
Bega, D., Gramaglia, M., Fiore, M., Banchs, A., and Costa-Perez, X. (2019). Deepcog: Cognitive network management in sliced 5g networks with deep learning. In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, pages 280–288.
Behringer, M. H., Pritikin, M., Bjarnason, S., Clemm, A., Carpenter, B. E., Jiang, S., and Ciavaglia, L. (2015). Autonomic Networking: Definitions and Design Goals. RFC 7575.
Benayas, F., Carrera, Á ., García-Amado, M., and Iglesias, C. A. (2019). A semantic data lake framework for autonomous fault management in sdn environments. Transactions on Emerging Telecommunications Technologies, 30(9):e3629.
Bencomo, N. and Blair, G. (2009). Using architecture models to support the generation and operation of component-based adaptive systems. In Software engineering for self-adaptive systems, pages 183–200. Springer.
Blair, G., Bencomo, N., and France, R. B. (2009). Models@ run.time. Computer, 42(10):22–27.
Eckert, T., Behringer, M. H., and Bjarnason, S. (2020). An Autonomic Control Plane (ACP). Internet-Draft draft-ietf-anima-autonomic-control-plane-30, Internet Engineering Task Force. Work in Progress.
Gelenbe, E. (2013). A software defined self-aware network: The cognitive packet network. In 2013 Ninth International Conference on Semantics, Knowledge and Grids, pages 1–5.
Gronback, R. C. (2009). Eclipse modeling project: a domain-specific language (DSL) toolkit. Pearson Education.
Jiang, S., Carpenter, B. E., and Behringer, M. H. (2015). General Gap Analysis for Autonomic Networking. RFC 7576.
Kalmbach, P., Zerwas, J., Babarczi, P., Blenk, A., Kellerer, W., and Schmid, S. (2018). Empowering self-driving networks. In Proceedings of the AfternoonWorkshop on Self-Driving Networks, pages 8–14. ACM.
Kalnins, A., Vilitis, O., Celms, E., Kalnina, E., Sostaks, A., and Barzdins, J. (2007). Building tools by model transformations in eclipse. In Proceedings of DSM, volume 7, pages 194–207.
Koutsouris, N., Tsagkaris, K., Demestichas, P., Mamatas, L., Clayman, S., and Galis, A. (2013). Managing software-driven networks with a unified management framework. In 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013), pages 1084–1085.
Kreutz, D., Ramos, F. M., Verissimo, P. E., Rothenberg, C. E., Azodolmolky, S., and Uhlig, S. (2014). Software-defined networking: A comprehensive survey. Proceedings of the IEEE, 103(1):14–76.
Li, H., Que, X., Hu, Y., Xiangyang, G., and Wendong, W. (2013). An autonomic management architecture for sdn-based multi-service network. In 2013 IEEE Globecom Workshops (GC Wkshps), pages 830–835.
Lopes, F. A., Santos, M., Fidalgo, R., and Fernandes, S. (2015). Model-driven networking: A novel approach for sdn applications development. In 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), pages 770–773.
Mestres, A., Rodriguez-Natal, A., Carner, J., Barlet-Ros, P., Alarcón, E., Solé, M., Muntés-Mulero, V., Meyer, D., Barkai, S., Hibbett, M. J., et al. (2017). Knowledge-defined networking. ACM SIGCOMM Computer Communication Review, 47(3):2–10.
Movahedi, Z., Ayari, M., Langar, R., and Pujolle, G. (2012). A survey of autonomic network architectures and evaluation criteria. IEEE Communications Surveys & Tutorials, 14(2):464–490.
Ochoa-Aday, L., Cervelló-Pastor, C., and Fernández-Fernández, A. (2019). Self-healing and sdn: bridging the gap. Digital Communications and Networks.
Poulios, G., Tsagkaris, K., Demestichas, P., Tall, A., Altman, Z., and Destr´e, C. (2014). Autonomics and sdn for self-organizing networks. In 2014 11th International Symposium on Wireless Communications Systems (ISWCS), pages 830–835.
Puterman, M. L. (2014). Markov decision processes: discrete stochastic dynamic programming. John Wiley & Sons.
Qi, Q., Wang, W., Gong, X., and Que, X. (2014). A sdn-based network virtualization architecture with autonomie management. In 2014 IEEE Globecom Workshops (GC Wkshps), pages 178–182.
Samaan, N. and Karmouch, A. (2009). Towards autonomic network management: an analysis of current and future research directions. IEEE Communications Surveys & Tutorials, 11(3):22–36.
Schaller, S. and Hood, D. (2017). Software defined networking architecture standardization. Computer Standards & Interfaces, 54:197–202.
Stamou, A., Dimitriou, N., Kontovasilis, K., and Papavassiliou, S. (2019). Autonomic handover management for heterogeneous networks in a future internet context: A survey. IEEE Communications Surveys & Tutorials.
Tessler, C., Efroni, Y., and Mannor, S. (2019). Action robust reinforcement learning and applications in continuous control. In International Conference on Machine Learning, pages 6215–6224. PMLR.
Tsagkaris, K., Logothetis, M., Foteinos, V., Poulios, G., Michaloliakos, M., and Demestichas, P. (2015). Customizable autonomic network management: Integrating autonomic network management and software-defined networking. IEEE Vehicular Technology Magazine, 10(1):61–68.
Tuncer, D., Charalambides, M., Clayman, S., and Pavlou, G. (2015). Adaptive resource management and control in software defined networks. IEEE Transactions on Network and Service Management, 12(1):18–33.
Volpato, F., Silva, M. P. D., Gonçalves, A. L., and Dantas, M. A. R. (2017). An autonomic qoe-aware management architecture for software-defined networking. In 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pages 220–225.
Wickboldt, J. A., De Jesus, W. P., Isolani, P. H., Both, C. B., Rochol, J., and Granville, L. Z. (2015). Software-defined networking: management requirements and challenges. IEEE Communications Magazine, 53(1):278–285.
Yahia, I. G. B., Bendriss, J., Samba, A., and Dooze, P. (2017). Cognitive 5g networks: Comprehensive operator use cases with machine learning for management operations. In 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN), pages 252–259.
Zhou, T., Xiangyang, G., Hu, Y., Que, X., and Wendong, W. (2013). Pindswitch: A sdn-based protocol-independent autonomic flow processing platform. In 2013 IEEE Globecom Workshops (GC Wkshps), pages 842–847.
Publicado
18/07/2021
Como Citar
LOPES, Felipe A..
Using the RFC 7575 and Models at Runtime for Enabling Autonomic Networking in SDN. In: WORKSHOP PRÉ-IETF (WPIETF), 8. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 13-26.
ISSN 2595-6388.
DOI: https://doi.org/10.5753/wpietf.2021.15779.
