Multi-Domain Network Intent Policy Enforcement

Ana Hermosilla^1,2,*, Pedro Martinez-Julia³, Diego R. Lopez⁴, Antonio F. Skarmeta^1,2
1 Information and Communications Engineering Department, University of Murcia, Murcia, 30100, Spain
2 Research & Development Department, Odin Solutions, Murcia, 30007, Spain
3 Network Architecture Laboratory, Network Research Institute, National Institute of Information and Communications Technology, Tokyo, 184-8795, Japan
4 Research & Development Department, Telefonica I+D, Madrid, 28050, Spain
* Corresponding Author: Ana Hermosilla. Email: email

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2025.072607

Received 30 August 2025; Accepted 04 November 2025; Published online 02 December 2025

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Abstract

In this study, we analyzed the processes involved in the resolution and enforcement of multi-domain network intent policies for intent-based networking (IBN). Previous studies on IBN analyzed the basis of the network intent resolution processes. These processes produce the artifacts required by network intent policy enforcement. Thus, we continued such studies with the inclusion of network intent policy enforcement in the analysis, for which we constructed a model that predicts the accuracy of a multi-domain network intent policy enforcement system. We validated the model by designing a new multi-domain network intent policy enforcement system, and evaluated the accuracy and performance of the new system through experimentation over a large-scale multi-domain platform that involves sites separated by more than ten thousand kilometers. The results show that, on the one hand, the new system improves accuracy by 10% and, on the other hand, that policies obtained from the multi-domain network intents, including the most complex ones, can be enforced in less than 1.75 s in a platform comprising sites located in almost opposite sides of the world. The experiment confirmed that the long distance existing between the sites involved in our experimental multi-domain IBN platform had little impact on the performance of the new system, and that the predictions obtained with the new model are as much as 99% accurate with respect to the behavior observed in the experiment.