Learning based energy efficient task offloading for vehicular collaborative edge computing
P Qin, Y Fu, G Tang, X Zhao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …
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 …
Deep-reinforcement-learning-based offloading scheduling for vehicular edge computing
Vehicular edge computing (VEC) is a new computing paradigm that has great potential to
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …
Computing on wheels: A deep reinforcement learning-based approach
Future generation vehicles equipped with modern technologies will impose unprecedented
computational demand due to the wide adoption of compute-intensive services with …
computational demand due to the wide adoption of compute-intensive services with …
Task offloading for vehicular edge computing with edge-cloud cooperation
Vehicular edge computing (VEC) is emerging as a novel computing paradigm to meet low
latency demands for computation-intensive vehicular applications. However, most existing …
latency demands for computation-intensive vehicular applications. However, most existing …
Delay-optimized V2V-based computation offloading in urban vehicular edge computing and networks
The Internet of Vehicles (IoV) is an emerging paradigm, driven by recent advancements in
vehicular communications and networking. Meanwhile, the capability and intelligence of …
vehicular communications and networking. Meanwhile, the capability and intelligence of …
Minimizing the delay and cost of computation offloading for vehicular edge computing
The development of autonomous driving poses significant demands on computing resource,
which is challenging to resource-constrained vehicles. To alleviate the issue, Vehicular …
which is challenging to resource-constrained vehicles. To alleviate the issue, Vehicular …
Deep learning-assisted energy-efficient task offloading in vehicular edge computing systems
In this paper, we study an energy-efficient computation offloading for vehicular edge
computing systems, where multiple roadside units assist vehicular users to offload …
computing systems, where multiple roadside units assist vehicular users to offload …
Distributed clustering-based cooperative vehicular edge computing for real-time offloading requests
Mobile vehicles have been considered as potential edge servers to provide computation
resources for the emerging Intelligent Transportation System (ITS) applications. However …
resources for the emerging Intelligent Transportation System (ITS) applications. However …
Deep reinforcement learning for collaborative edge computing in vehicular networks
Mobile edge computing (MEC) is a promising technology to support mission-critical
vehicular applications, such as intelligent path planning and safety applications. In this …
vehicular applications, such as intelligent path planning and safety applications. In this …