[HTML][HTML] A comprehensive survey on reinforcement-learning-based computation offloading techniques in Edge Computing Systems
In recent years, the number of embedded computing devices connected to the Internet has
exponentially increased. At the same time, new applications are becoming more complex …
exponentially increased. At the same time, new applications are becoming more complex …
Dependent task scheduling and offloading for minimizing deadline violation ratio in mobile edge computing networks
S Liu, Y Yu, X Lian, Y Feng, C She… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
This paper considers computation offloading for mobile applications with task-dependency
requirements in mobile edge computing (MEC) systems. Based on the online arrival patterns …
requirements in mobile edge computing (MEC) systems. Based on the online arrival patterns …
RFID: Towards low latency and reliable DAG task scheduling over dynamic vehicular clouds
Vehicular cloud (VC) platforms integrate heterogeneous and distributed resources of moving
vehicles to offer timely and cost-effective computing services. However, the dynamic nature …
vehicles to offer timely and cost-effective computing services. However, the dynamic nature …
Deep Reinforcement Learning Based Distributed Computation Offloading in Vehicular Edge Computing Networks
L Geng, H Zhao, J Wang, A Kaushik… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Vehicular edge computing has emerged as a promising paradigm by offloading computation-
intensive latency-sensitive tasks to mobile-edge computing (MEC) servers. However, it is …
intensive latency-sensitive tasks to mobile-edge computing (MEC) servers. However, it is …
GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds
Vehicular Clouds (VCs) are modern platforms for processing of computation-intensive tasks
over vehicles. Such tasks are often represented as Directed Acyclic Graphs (DAGs) …
over vehicles. Such tasks are often represented as Directed Acyclic Graphs (DAGs) …
Dependency-aware task cooperative offloading on edge servers interconnected by metro optical networks
Multi-access edge computing is a promising technology for solving delay sensitive,
computationally intensive applications. It aids users with low-latency access by deploying …
computationally intensive applications. It aids users with low-latency access by deploying …
Uncertainty-aware task offloading for multi-vehicle perception fusion over vehicular edge computing
Multi-vehicle perception fusion is an emerging advanced vehicular application providing
Vehicle Users (VUs) with comprehensive driving assistance. This involves each VU's …
Vehicle Users (VUs) with comprehensive driving assistance. This involves each VU's …
Reliable adaptive edge-cloud collaborative DNN inference acceleration scheme combining computing and communication resources in optical networks
S Yin, Y Jiao, C You, M Cai, T Jin… - Journal of Optical …, 2023 - opg.optica.org
With the continuous development of the Artificial Intelligence of Things, deep neural network
(DNN) models require a larger amount of computing capacity. The emerging edge-cloud …
(DNN) models require a larger amount of computing capacity. The emerging edge-cloud …
AI 算法在车联网通信与计算中的应用综述
康宇， 刘雅琼， 赵彤雨， 寿国础 - 电信科学, 2023 - infocomm-journal.com
在5G 时代, 车联网的通信和计算发展受到信息量急速增加的限制. 将AI 算法应用在车联网,
可以实现车联网通信和计算方面的新突破. 调研了AI 算法在通信安全, 通信资源分配 …
可以实现车联网通信和计算方面的新突破. 调研了AI 算法在通信安全, 通信资源分配 …
Towards Risk-Averse Edge Computing With Deep Reinforcement Learning
Recently, artificial intelligence paves the way for the development of smart services for
people anytime and anywhere, which poses great challenges on accessing computing …
people anytime and anywhere, which poses great challenges on accessing computing …