Digital twin-assisted resource allocation framework based on edge collaboration for vehicular edge computing
Abstract Vehicular Edge Computing (VEC) supports latency-sensitive and computation-
intensive vehicular applications by providing caching and computing services in vehicle …
intensive vehicular applications by providing caching and computing services in vehicle …
Multi-objective secure task offloading strategy for blockchain-enabled IoV-MEC systems: a double deep Q-network approach
The Internet of Vehicles (IoV) represents a paradigm shift in vehicular communication,
aiming to enhance traffic efficiency, safety, and the driving experience by leveraging …
aiming to enhance traffic efficiency, safety, and the driving experience by leveraging …
Resource Allocation for Twin Maintenance and Computing Task Processing in Digital Twin Vehicular Edge Computing Network
As a promising technology, vehicular edge computing (VEC) can provide computing and
caching services by deploying VEC servers near vehicles. However, VEC networks still face …
caching services by deploying VEC servers near vehicles. However, VEC networks still face …
Joint Accuracy and Latency Optimization for Quantized Federated Learning in Vehicular Networks
Nowadays, vehicular networks have emerged as a boosting technology to enhance traffic
efficiency and safety within transportation systems. As the amount of onboard data increases …
efficiency and safety within transportation systems. As the amount of onboard data increases …
Cooperative Computation Offloading and Resource Management for Vehicle Platoon: A Deep Reinforcement Learning Approach
L Lu, X Li, J Sun, Z Yang - 2022 IEEE 24th Int Conf on High …, 2022 - ieeexplore.ieee.org
On the Internet of Vehicles, the computation capability of individual vehicle is restricted to
finish upcoming vehicular computational tasks. Fortunately, vehicular edge computing (VEC) …
finish upcoming vehicular computational tasks. Fortunately, vehicular edge computing (VEC) …
Efficient DRL-Based Selection Strategy in Hybrid Vehicular Networks
BY Yacheur, T Ahmed… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Emerging V2X applications, like Advanced Driver Assistance Systems (ADASs) and
Connected Autonomous Driving (CAD) require Ultra-Reliable Low Latency Communications …
Connected Autonomous Driving (CAD) require Ultra-Reliable Low Latency Communications …
Augmented Intelligence of Things for Priority-Aware Task Offloading in Vehicular Edge Computing
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 …
transportation services due to limited computing resources at VEC servers, which lead to …
A Hybrid Deep Reinforcement Learning Approach for Jointly Optimizing Offloading and Resource Management in Vehicular Networks
CL Chen, B Bhargava, V Aggarwal… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Satisfying the quality of service of data-intensive autonomous driving applications has
become challenging. In this work, we propose a novel methodology that optimizes …
become challenging. In this work, we propose a novel methodology that optimizes …
Learning based energy efficient task offloading for vehicular collaborative edge computing
Extensive delay-sensitive and computation-intensive tasks are involved in emerging
vehicular applications. These tasks can hardly be all processed by the resource constrained …
vehicular applications. These tasks can hardly be all processed by the resource constrained …
An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning
L Zhu, L Tan, B Li, H Tian - IET Communications, 2024 - Wiley Online Library
Traditional vehicular edge computing research usually ignores the mobility of vehicles, the
dynamic variability of the vehicular edge environment, the large amount of real‐time data …
dynamic variability of the vehicular edge environment, the large amount of real‐time data …