An end-to-end network slicing design policy

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Abstract

Network Slicing is regarded as a promising tech-nology to provide required services for different application scenarios by means of supporting multiple slices to embed the underlying physical network. However, it is still a challenging task to design network slicing aiming at providing specific services for different types of tenants while making efficient use of physical resources. Thus, the paper attempts to tackle the problem by proposing a novel end-to-end network slicing design policy. We start from modeling the mathematical model of the physical network and network slicing requests by using the Formal Concept Analysis methodology. Then, multiple design objectives for various use cases are defined, and the relevant resource constraints are also provided. Moreover, we propose a meta-heuristic algorithm based on the Multi-Objective Particle Swarm Optimization for the network slicing design problem. Extensive simulations illustrate that the resource efficiency of our proposed algorithm is better than the existing algorithms in terms of both node and link resources utilization.

Original languageEnglish
Title of host publication2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728144900
DOIs
Publication statusPublished - Aug 2020
Event31st IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2020 - Virtual, London, United Kingdom
Duration: 31 Aug 20203 Sept 2020

Publication series

NameIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Volume2020-August

Conference

Conference31st IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2020
Country/TerritoryUnited Kingdom
CityVirtual, London
Period31/08/20203/09/2020

Keywords

  • Formal Concept Analysis
  • Mapping
  • Multi-Objective Particle Swarm Optimization
  • Network Slicing

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