Abstract
One of the challenges of the Network Functions Virtualization (NFV) paradigm is to deploy virtualized network functions and services efficiently. In particular, current solutions for multi-domain service mapping present several restrictions regarding the choice of optimization models and metrics. This lack of flexibility ultimately leads to sub-optimized mappings that do not meet the (often conflicting) requirements of all the parties involved in the deployment process (e.g., network operators, clients, providers). This work proposes GeSeMa (Genetic Service Mapping), a new intelligent mapping solution based on genetic algorithms. GeSeMa allows the specification of arbitrary optimization metrics, constraints, and different evaluation policies. We evaluate GeSeMa through a case study, comparing its results with the results of a state-of-the-art genetic-based mapping solution.
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Notes
- 1.
The implementation is available at https://github.com/ViniGarcia/NFV-FLERAS.
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Fulber-Garcia, V., Luizelli, M.C., dos Santos, C.R.P., Spinosa, E.J., Duarte, E.P. (2023). Intelligent Mapping of Virtualized Services on Multi-domain Networks. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 646. Springer, Cham. https://doi.org/10.1007/978-3-031-27440-4_46
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