Digital Twin-assisted Space-Air-Ground Integrated Networks for Vehicular Edge Computing

A Paul, K Singh, MHT Nguyen, C Pan… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
In this paper, we present a framework that integrates digital twin (DT) technology into space-
air-ground integrated networks (SAGINs) to enhance vehicular edge computing (VEC). Our …

Task Offloading and Resource Allocation in Vehicular Networks: A Lyapunov-based Deep Reinforcement Learning Approach

AS Kumar, L Zhao, X Fernando - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) has gained popularity due to its ability to enhance
vehicular networks. VEC servers located at Roadside Units (RSUs) allow low-power …

Digital Twin-Aided Vehicular Edge Network: A Large-Scale Model Optimization by Quantum-DRL

A Paul, K Singh, CP Li, OA Dobre… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This paper presents an innovative large model framework for optimizing the task offloading
efficiency in vehicular edge networks, with a focus on ultra-reliable lowlatency …

Adaptive digital twin and multiagent deep reinforcement learning for vehicular edge computing and networks

K Zhang, J Cao, Y Zhang - IEEE Transactions on Industrial …, 2021 - ieeexplore.ieee.org
Technological advancements of urban informatics and vehicular intelligence have enabled
connected smart vehicles as pervasive edge computing platforms for a plethora of powerful …

[PDF][PDF] Decentralized vehicular edge computing framework for energy-efficient task coordination

M Fardad, GM Muntean, I Tal - 2024 IEEE 99th Vehicular …, 2024 - researchgate.net
Vehicular edge computing (VEC) empowers realtime applications in the autonomous
vehicle (AV) domain by positioning edge servers closer to AVs. This proximity reduces …

Asynchronous federated deep reinforcement learning-based URLLC-aware computation offloading in space-assisted vehicular networks

C Pan, Z Wang, H Liao, Z Zhou, X Wang… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Space-assisted vehicular networks (SAVN) provide seamless coverage and on-demand
data processing services for user vehicles (UVs). However, ultra-reliable and low-latency …

Augmented Intelligence of Things for Priority-Aware Task Offloading in Vehicular Edge Computing

X Wang, J Lv, A Slowik, BG Kim… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Vehicular edge computing (VEC) systems face challenges in providing real-time intelligent
transportation services due to limited computing resources at VEC servers, which lead to …

Learning-based load-aware heterogeneous vehicular edge computing

L Zhu, Z Zhang, P Lin, O Shafiq… - … 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Vehicular edge computing is an emerging enabler to support vehicular-based computation-
intensive tasks. By reason of the time-varying vehicular wireless environments and the …

HAP-assisted RSMA-enabled vehicular edge computing: A DRL-based optimization framework

TH Nguyen, L Park - Mathematics, 2023 - mdpi.com
In recent years, the demand for vehicular edge computing (VEC) has grown rapidly due to
the increasing need for low-latency and high-throughput applications such as autonomous …

Federated deep reinforcement learning based task offloading with power control in vehicular edge computing

S Moon, Y Lim - Sensors, 2022 - mdpi.com
Vehicular edge computing (VEC) is a promising technology for supporting computation-
intensive vehicular applications with low latency at the network edges. Vehicles offload their …