Dynamic task offloading with minority game for Internet of Vehicles in cloud-edge computing

Bowen Shen, Xiaolong Xu*, Fei Dar, Lianyong Qi, Xuyun Zhang, Wanchun Dou

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

With the advent of the Internet of Vehicles (IoV), drivers are now provided with diverse time-sensitive vehicular services that usually require a large scale of computation. As civilian vehicles are generally insufficient in computational resources, their service requests are offloaded to cloud data centers and edge computing devices (ECDs) with ample computational resources to enhance the quality of service (QoS). However, ECDs are often overloaded with excessive service requests. In addition, as the network conditions and service compositions are complicated and dynamic, the centralized control of ECDs is hard to achieve. To tackle these challenges, a dynamic task offloading method with minority game (MG) in cloud-edge computing, named DOM, is proposed in this paper. Technically, MG is an effective tool with a distributed mechanism which can minimize the dependency on centralized control in resource allocation. In the MG, reinforcement learning (RL) is applied to optimize the distributed decision-making of participants. Finally, with a real-world dataset of IoV services, the effectiveness and adaptability of DOM are evaluated.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 13th International Conference on Web Services, ICWS 2020
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages372-379
Number of pages8
ISBN (Electronic)9781728187860
DOIs
Publication statusPublished - 2020
Event13th IEEE International Conference on Web Services, ICWS 2020 - Virtual, Beijing, China
Duration: 18 Oct 202024 Oct 2020

Publication series

NameProceedings - 2020 IEEE 13th International Conference on Web Services, ICWS 2020

Conference

Conference13th IEEE International Conference on Web Services, ICWS 2020
CountryChina
CityVirtual, Beijing
Period18/10/2024/10/20

Keywords

  • Dynamic Task Offloading
  • Edge Computing
  • Game Theory
  • Reinforcement Learning

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