Priority-Based Dynamic Resource Allocation Scheme in Network Slicing

Haneul Ko, Jaewook Lee, Sangheon Pack

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the network slicing environment, if insufficient resource is allocated to a resource-hungry slice (e.g., ultrareliable low latency communication (URLLC)), its quality of service (QoS) can be significantly degraded. In this paper, we propose a priority-based dynamic resource allocation scheme (PDRAS) where the resource management agent maintains some information such as priorities and demand profiles of slices. Based on these information, the agent dynamically allocates resources to slices. To maximize QoS of slices while maintaining the total amount of allocated resources below a certain level, a constrained Markov decision process (CMDP) problem is formulated and the optimal allocation policy is achieved by linear programming (LP). Extensive evaluation results are given to demonstrate the effectiveness of PDRAS with the optimal policy compared to that of other schemes in terms of QoS and the efficiency of the resource usage.

Original languageEnglish
Title of host publication35th International Conference on Information Networking, ICOIN 2021
PublisherIEEE Computer Society
Pages62-64
Number of pages3
ISBN (Electronic)9781728191003
DOIs
Publication statusPublished - 2021 Jan 13
Event35th International Conference on Information Networking, ICOIN 2021 - Jeju Island, Korea, Republic of
Duration: 2021 Jan 132021 Jan 16

Publication series

NameInternational Conference on Information Networking
Volume2021-January
ISSN (Print)1976-7684

Conference

Conference35th International Conference on Information Networking, ICOIN 2021
Country/TerritoryKorea, Republic of
CityJeju Island
Period21/1/1321/1/16

Keywords

  • Network slicing
  • constrained Markov decision process (CMDP)
  • quality of service (QoS)
  • resource allocation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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