Closed-Loop Network Automation: Architectural Principles for Intent-Based Networking
Abstract
Closed-loop network automation offers networking systems to ensure that the desired results are coded in the observation, analysis, corrective action, and verification continuously. However, achieving reliable autonomy is challenging because network telemetry is not exhaustive, and control actions can have an indirect effect, and multiple loops of automation can all act on shared resources. This study proposes a safe and regulated intent-based networking architectural design that incorporates authoritative intent state, monitored operational state, analytic diagnosis, limited planning, regulated execution, and verified post-action validation. The design offers clear ownership of the loops in the structure, time isolation, and evaluation of confidence, blast-radius limit, roll-back, and human supervision to limit unexpected impacts. A major architectural consideration is that autonomy must be delegated based on classes of action and risk, as opposed to being delegated equally throughout a complete automation platform. The evaluation methodology presented in this study also describes the evaluation methodology dimensions with the following outcome-satisfaction, control-loop stability, false-action level, recovery time, and policy-compliance core-assessment dimensions. With intent management, closed-loop control, operational safeguards, and continuous verification, the proposed architecture makes network automation a controlled system with adaptive remediation that ensures operational stability and accountability, as well as stays aligned with the policy
Article Information
Journal |
International Journal of Future Innovative Science and Technology (IJFIST) |
|---|---|
Volume (Issue) |
Vol. 5 No. 5 (2022): International Journal of Future Innovative Science and Technology (IJFIST) |
DOI |
|
Pages |
9284-9294 |
Published |
September 19, 2022 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Manevannan Ramasamy (2022). Closed-Loop Network Automation: Architectural Principles for Intent-Based Networking. International Journal of Future Innovative Science and Technology (IJFIST) , Vol. 5 No. 5 (2022): International Journal of Future Innovative Science and Technology (IJFIST) , pp. 9284-9294. https://doi.org/10.15662/IJFIST.2022.0505010 |
References
[2] J. O. Kephart and D. M. Chess, “The vision of autonomic computing,” Computer, vol. 36, no. 1, pp. 41–50, 2003. https://doi.org/10.1109/MC.2003.1160055
[3] M. Behringer et al., “Autonomic Networking Definitions and Design Goals,” RFC 7575, Jun. 2015. https://doi.org/10.17487/RFC7575
[4] Q. Wu et al., “A Framework for Automating Service and Network Management with YANG,” RFC 8969, Jan. 2021. https://doi.org/10.17487/RFC8969
[5] ETSI, “Zero Touch Network and Service Management Reference Architecture,” ETSI GS ZSM 002 V1.1.1, Aug. 2019. https://www.etsi.org/deliver/etsi_gs/ZSM/001_099/002/01.01.01_60/gs_ZSM002v010101p.pdf
[6] M. Kiran et al., “Enabling intent to configure scientific networks for high performance demands,” Future Generation Computer Systems, vol. 79, pp. 561–574, 2018.
[7] M. Chen et al., “Automatic deployment and control of network services in NFV environments,” Journal of Network and Computer Applications, vol. 167, 2020.
[8] T. Kohler et al., “A highly flexible and modular architecture for full-range distribution of event-based network control,” IEEE Transactions on Network and Service Management, vol. 15, no. 4, pp. 1392–1405, 2018.
[9] W. Guan et al., “A service-oriented deployment policy of end-to-end network slicing based on complex network theory,” IEEE Access, vol. 6, pp. 72403–72413, 2018.
[10] P. Kokkinos et al., “Pattern-driven resource allocation in optical networks,” IEEE Transactions on Network and Service Management, vol. 16, no. 2, pp. 616–629, 2019.