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

  • Institut Mines-Télécom
  • Technological Research Institute SystemX

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

41 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationCCNC 2018 - 2018 15th IEEE Annual Consumer Communications and Networking Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647905
DOIs
Publication statusPublished - 16 Mar 2018
Externally publishedYes
Event15th IEEE Annual Consumer Communications and Networking Conference, CCNC 2018 - Las Vegas, United States
Duration: 12 Jan 201815 Jan 2018

Publication series

NameCCNC 2018 - 2018 15th IEEE Annual Consumer Communications and Networking Conference
Volume2018-January

Conference

Conference15th IEEE Annual Consumer Communications and Networking Conference, CCNC 2018
Country/TerritoryUnited States
CityLas Vegas
Period12/01/1815/01/18

Keywords

  • Chains Placement
  • Forwarding Graph
  • NFV
  • NSGA-II
  • Optimization

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