Digital Twin-Assisted Resource Allocation in UAV-Aided Internet of Vehicles Networks

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publication2023 IEEE International Conference on Communications Workshops (ICC Workshops)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages409-414
ISBN (Electronic)9798350333077
ISBN (Print)9798350333084
Publication statusPublished - 2023

Publication series

NameIEEE International Conference on Communications Workshops: Sustainable Communications for Renaissance, ICC Workshops
ISSN (Print)2164-7038
ISSN (Electronic)2694-2941

Conference

Title2023 IEEE International Conference on Communications Workshops (ICCW 2023)
PlaceItaly
CityRome
Period28 May - 1 June 2023

Abstract

In this paper, we consider an Internet of Vehicles (IoV) network, whereby unmanned aerial vehicles (UAVs) assist mobile edge computing (MEC) servers of the roadside units (RSUs) to provide ubiquitous connectivity to the vehicles. A virtual representation of the IoV network is established in the aerial network as a digital twin (DT) which captures the dynamics of the entities of the physical network in real-time in order to perform efficient resource allocation. For this, we investigate an intelligent delay-sensitive task offloading scheme for the dynamic vehicular environment which provides computation resources via local execution, vehicle-to-vehicle (V2V), and vehicle-to-infrastructure/RSU (V2I) offloading modes based on the energy consumption of the system. We propose a deep reinforcement learning (DRL)-based resource allocation scheme in the DT (RADiT) of the IoV network for maximizing its utility while optimizing the strategy of task offloading. We compare the performance of the proposed algorithm with and without the presence of V2V computation mode and another benchmark, DRL algorithm called soft actor-critic (SAC). Finally, simulations are performed to demonstrate the efficacy of the proposed RADiT algorithm. © 2023 IEEE.

Research Area(s)

  • deep reinforcement learning (DRL), Internet of vehicles (IoV), mobile edge computing(MEC)

Citation Format(s)

Digital Twin-Assisted Resource Allocation in UAV-Aided Internet of Vehicles Networks. / Singh, Keshav; Hazarika, Bishmita; Li, Chih-Peng et al.
2023 IEEE International Conference on Communications Workshops (ICC Workshops). Institute of Electrical and Electronics Engineers Inc., 2023. p. 409-414 (IEEE International Conference on Communications Workshops: Sustainable Communications for Renaissance, ICC Workshops).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review