Joint optimization for latency minimization in UAV-assisted MEC networks

Chen Wang, Ruonan Zhang, Haotong Cao, Junhao Song, Wei Zhang

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

3 Scopus citations

Abstract

Combining unmanned aerial vehicles (UAVs) with multi-access edge computing (MEC) networks has been deemed as a potential approach for delay-sensitive applications. In this paper, we propose a UAV-assisted MEC network architecture and jointly optimize the UAVs' position, task offloading, bandwidth allocation, and computing resource allocation to minimize the time consumption of each terminal devices cluster. To solve this problem, we design a joint optimization algorithm based on the particle swarm optimization (PSO) and bisection searching (BSS) approach. The results of the simulation reveal that the devised algorithm can significantly reduce time consumption and guarantee the fairness of the whole network.

Original languageEnglish
Title of host publicationDroneCom 2022 - Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond
PublisherAssociation for Computing Machinery, Inc
Pages19-24
Number of pages6
ISBN (Electronic)9781450395144
DOIs
StatePublished - 24 Oct 2022
Event5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond, DroneCom 2022 - Sydney, Australia
Duration: 21 Oct 2022 → …

Publication series

NameDroneCom 2022 - Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond

Conference

Conference5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond, DroneCom 2022
Country/TerritoryAustralia
CitySydney
Period21/10/22 → …

Keywords

  • MEC
  • UAV
  • joint optimization
  • latency minimization

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