QoS Aware Slice Resource Management Using Deep Reinforcement Learning in IoT Networks

Kamran Zia, Alessandro Chiumento, Paul J.M. Havinga, Roberto Riggio, Yanqiu Huang

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

1 Citation (Scopus)
11 Downloads (Pure)

Abstract

WiFi, a widely used technology in IoT, provides QoS through IEEE 802.11e EDCA Access Categories (AC) which have fixed configuration with strict priorities. This makes WiFi QoS unsuitable to the rising QoS diversity, changing wireless conditions and network dynamics. QoS slicing, where network resources are divided into chinks for diverse QoS requirements, is a potent technology that can provide more flexible, adaptable and highly configurable QoS in WiFi based IoT networks. However, resource management of QoS slices with diverse IoT applications, limited network capacity and varying channel conditions is a complex and challenging task. Traditional queuing theoretic and optimization models become intractable to solve such complex and dynamic problem. Therefore, we have developed a Deep Reinforcement Learning (DRL) based slice resource management scheme to meet IoT QoS requirements in a real world 5GEmpower controlled SDN network. Our proposed scheme outperforms Airtime Excess Round Robin (ATERR) scheme and no slicing-based scheme in terms of slice throughput (QoS) satisfaction. Moreover, our proposed scheme is tested in real world environment and can adapt to the changing slice requirements in an IoT network.
Original languageEnglish
Title of host publicationQoS Aware Slice Resource Management Using Deep Reinforcement Learning in IoT Networks
Pages150-154
Number of pages5
ISBN (Electronic)979-8-3503-4649-7
DOIs
Publication statusPublished - 27 Sept 2023
Event19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023 - Paphos, Cyprus
Duration: 19 Jun 202321 Jun 2023
Conference number: 19
https://dcoss.org/dcoss23/

Publication series

Name 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)
PublisherIEEE
ISSN (Print)2325-2936
ISSN (Electronic)2325-2944

Conference

Conference19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
Abbreviated titleDCOSS-IoT 2023
Country/TerritoryCyprus
CityPaphos
Period19/06/2321/06/23
Internet address

Keywords

  • Deep Learning
  • Wireless communication
  • Quality of service
  • Reinforcement learning
  • IoT Networks
  • Resource Management
  • 2023 OA procedure

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