DNN Partitioning, Task Offloading, and Resource Allocation in Dynamic Vehicular Networks: A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach
The rapid advancement of Artificial Intelligence (AI) has introduced Deep Neural Network
(DNN)-based tasks to the ecosystem of vehicular networks. These tasks are often …
(DNN)-based tasks to the ecosystem of vehicular networks. These tasks are often …
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 …
vehicular networks. VEC servers located at Roadside Units (RSUs) allow low-power …
[PDF][PDF] Task offloading and proactive resource allocation in vehicular edge computing via reinforcement learning
E Karimi - 2022 - research.library.mun.ca
Given the rapid increase of various applications in vehicular networks, it is crucial to
consider a flexible architecture to improve the Quality-of-Service (QoS). Utilizing Multi …
consider a flexible architecture to improve the Quality-of-Service (QoS). Utilizing Multi …
A fast-adaptive edge resource allocation strategy for dynamic vehicular networks
With the rapid development of vehicular networks, there is an increasing demand for
extensive networking, computing and caching resources. In fact, vehicular networks are …
extensive networking, computing and caching resources. In fact, vehicular networks are …
Deep Reinforcement Learning-Based Task Offloading for Vehicular Edge Computing With Flexible RSU-RSU Cooperation
W Fan, Y Zhang, G Zhou, Y Liu - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Vehicle edge computing (VEC) acts as an enhancement to provide low latency and low
energy consumption for internet of vehicles (IoV) applications. Mobility of vehicles and load …
energy consumption for internet of vehicles (IoV) applications. Mobility of vehicles and load …
Toward reliable dnn-based task partitioning and offloading in vehicular edge computing
Modern vehicles have become typical consumer electronics with the development of
sensing, transmission, and computation technologies. The emerging intelligent …
sensing, transmission, and computation technologies. The emerging intelligent …
Asynchronous deep reinforcement learning for collaborative task computing and on-demand resource allocation in vehicular edge computing
Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …
[PDF][PDF] Decentralized Multi-layer Vehicular Edge Computing Framework for Time-Efficient Task Coordination
Vehicle edge computing (VEC) offers substantial potential to enhance real-time applications
in the connected autonomous vehicle (CAV) sector by positioning edge servers near CAVs …
in the connected autonomous vehicle (CAV) sector by positioning edge servers near CAVs …
Value decomposition based multi-task multi-agent deep reinforcement learning in vehicular networks
With the development of intelligent transportation system (ITS), a multitude of novel vehicular
applications have been emerging. There is an urgent need for simultaneously supporting …
applications have been emerging. There is an urgent need for simultaneously supporting …
Accelerating dnn inference with reliability guarantee in vehicular edge computing
This paper explores on accelerating Deep Neural Network (DNN) inference with reliability
guarantee in Vehicular Edge Computing (VEC) by considering the synergistic impacts of …
guarantee in Vehicular Edge Computing (VEC) by considering the synergistic impacts of …