Abstract
Software-Defined Networking exploits Network Function Virtualization to face the challenges of modern enterprise networks, integrating cloud and Internet of Things deployments. Conventional methodologies are often inadequate, whereas novel approaches based on Artificial Intelligence can achieve the required levels of flexibility and scalability. This paper presents a network orchestration and management framework based on Semantic Web languages and technologies. The proposal adopts a two-level ontology design: (i) a novel translator automatically generates a low-layer ontology from the YANG network information model; (ii) a high-level domain ontology is introduced to model the contextual scenario knowledge. In early tests, a prototypical implementation of the proposed framework has exploited SWRL rules to check network requirements against metrics and constraints, in order to detect violations and provide context-aware suggestions for corrective actions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bjorklund, M.: The YANG 1.1 data modeling language. RFC 7950, Internet Engineering Task Force (2016)
Bjorklund, M., Berger, L.: YANG Tree Diagrams. RFC 8340, Internet Engineering Task Force (2018)
Bonfim, M., Freitas, F., Fernandes, S.: A semantic-based policy analysis solution for the deployment of NFV services. IEEE Trans. Netw. Serv. Manage. 16(3), 1005–1018 (2019)
Enns, R., Bjorklund, M., Schoenwaelder, J.: NETCONF configuration protocol. RFC 4741, Internet Engineering Task Force (2006)
Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A Semantic Web Rule Language Combining OWL and RuleML. W3C Member Submission, W3C (2014), https://www.w3.org/Submission/SWRL/
Kim, S.I., Kim, H.S.: Semantic ontology-based NFV service modeling. In: 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN), pp. 674–678. IEEE (2018)
Kojukhov, A., et al.: Network functions virtualisation (NFV) release 2; protocols and data models; VNF package specification. GS NFV-SOL 004 v2. 3.1. Group specification, ETSI (2017)
Lamy, J.B.: Owlready: ontology-oriented programming in python with automatic classification and high level constructs for biomedical ontologies. Artif. Intell. Med. 80, 11–28 (2017)
Latah, M., Toker, L.: Artificial intelligence enabled software-defined networking: a comprehensive overview. IET Netw. 8(2), 79–99 (2019)
Lhotka, L.: JSON Encoding of Data Modeled with YANG. Technical Report 7951 (2016). https://doi.org/10.17487/RFC7951, https://www.rfc-editor.org/info/rfc7951
Lopez, V., et al.: Transport API: a solution for SDN in carriers networks. In: ECOC 2016; 42nd European Conference on Optical Communication, pp. 1–3. VDE (2016)
Molina Zarca, A., Bagaa, M., Bernal Bernabe, J., Taleb, T., Skarmeta, A.F.: Semantic-aware security orchestration in SDN/NFV-enabled IoT systems. Sensors 20(13), 3622 (2020)
Musen, M.A.: The Protégé project: a look back and a look forward. AI Matters 1(4), 4–12 (2015)
Oliver, I., Panda, S., Wang, K., Kalliola, A.: Modelling NFV concepts with ontologies. In: 2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), pp. 1–7. IEEE (2018)
Parsia, B., Rudolph, S., Krötzsch, M., Patel-Schneider, P., Hitzler, P.: OWL 2 Web Ontology Language Primer (Second Edition). W3C Recommendation, W3C (2012). http://www.w3.org/TR/owl2-primer
Sacramento, E.R., Vidal, V.M., de Macêdo, J.A.F., Lóscio, B.F., Lopes, F.L.R., Casanova, M.A.: Towards automatic generation of application ontologies. J. Inf. Data Manage. 1(3), 535–535 (2010)
Sendra, S., Rego, A., Lloret, J., Jimenez, J.M., Romero, O.: Including artificial intelligence in a routing protocol using software defined networks. In: 2017 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 670–674. IEEE (2017)
Sirin, E., Parsia, B., Cuenca Grau, B., Kalyanpur, A., Katz, Y.: Pellet: a practical OWL-DL reasoner. J. Web Semant. 5(2), 51–53 (2007)
Xiang, W., Wang, N., Zhou, Y.: An energy-efficient routing algorithm for software-defined wireless sensor networks. IEEE Sens. J. 16(20), 7393–7400 (2016)
Acknowledgments
This work has been supported by Italian PON project NGS (New Satellites Generation Components).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ieva, S., Loconte, D., Pinto, A., Scioscia, F., Ruta, M. (2023). Semantic-Based Decision Support for Network Management and Orchestration. In: Agapito, G., et al. Current Trends in Web Engineering. ICWE 2022. Communications in Computer and Information Science, vol 1668. Springer, Cham. https://doi.org/10.1007/978-3-031-25380-5_10
Download citation
DOI: https://doi.org/10.1007/978-3-031-25380-5_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-25379-9
Online ISBN: 978-3-031-25380-5
eBook Packages: Computer ScienceComputer Science (R0)