A multi-objective non-dominated sorting genetic algorithm for VNF chains placement

Abstract : We propose a meta-heuristic based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to address the NP-Hard service function chain placement problem. This work considers the minimization of the mapping cost and of the physical links utilization for virtualized network functions (VNF) chaining. The proposed NSGA-II based algorithm finds a Pareto front to select solutions that meet the multiple objectives and performance tradeoffs of providers. Simulation results and comparison with a multi-stage algorithm and a matrix based heuristic from the literature, highlight the efficiency and usefulness of the proposed NSGA-II-based approach
Type de document :
Communication dans un congrès
CCNC 2018 : IEEE Consumer Communications & Networking Conference, Jan 2018, Las Vegas, United States. 2018, 〈10.1109/CCNC.2018.8319250〉
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https://hal.archives-ouvertes.fr/hal-01613473
Contributeur : Makhlouf Hadji <>
Soumis le : lundi 9 octobre 2017 - 16:16:36
Dernière modification le : mercredi 5 septembre 2018 - 15:18:44

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Selma Khebbache, Makhlouf Hadji, Zeghlache Djamal. A multi-objective non-dominated sorting genetic algorithm for VNF chains placement. CCNC 2018 : IEEE Consumer Communications & Networking Conference, Jan 2018, Las Vegas, United States. 2018, 〈10.1109/CCNC.2018.8319250〉. 〈hal-01613473〉

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