A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches
Driven by the demand of time-sensitive and data-intensive applications, edge computing
has attracted wide attention as one of the cornerstones of modern service architectures. An …
has attracted wide attention as one of the cornerstones of modern service architectures. An …
Survey on task-centric robot battery management: A neural network framework
The surge in autonomous robotic applications across various sectors highlights the crucial
need for effective robot battery management to ensure robots perform their tasks …
need for effective robot battery management to ensure robots perform their tasks …
MCOTM: Mobility-aware computation offloading and task migration for edge computing in industrial IoT
Mobility-aware devices are crucial components of Industrial Internet of Things (IIoT).
However, they face limitations in terms of battery capacity and computation power, which …
However, they face limitations in terms of battery capacity and computation power, which …
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) …
Joint task offloading, resource allocation, and trajectory design for multi-uav cooperative edge computing with task priority
H Hao, C Xu, W Zhang, S Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Mobile edge computing (MEC) has emerged as a solution to address the demands of
computation-intensive network services by providing computational capabilities at the …
computation-intensive network services by providing computational capabilities at the …
Double RISs assisted task offloading for NOMA-MEC with action-constrained deep reinforcement learning
J Fang, B Lu, X Hong, J Shi - Knowledge-Based Systems, 2024 - Elsevier
Reconfigurable intelligent surface (RIS) is expected to enhance task offloading performance
in non-line-of-sight mobile edge computing (MEC) scenarios. This paper aims at reducing …
in non-line-of-sight mobile edge computing (MEC) scenarios. This paper aims at reducing …
Multi-cluster Cooperative Offloading for VR Task: A MARL Approach with Graph Embedding
Virtual reality (VR) technology has recently achieved notable success and been widely
expected to interplay with more mobile multimedia services. To further enhance real-time …
expected to interplay with more mobile multimedia services. To further enhance real-time …
Priority-aware path planning and user scheduling for UAV-mounted MEC networks: A deep reinforcement learning approach
X Zheng, Y Wu, L Zhang, M Tang, F Zhu - Physical Communication, 2024 - Elsevier
Owing to the flexibility and controllability, unmanned aerial vehicle (UAV) is frequently
integrated into mobile edge computing (MEC) network to improve the system performance …
integrated into mobile edge computing (MEC) network to improve the system performance …
An efficient scheduling scheme for intelligent driving tasks in a novel vehicle-edge architecture considering mobility and load balancing
N Wang, S Pang, X Ji, H Gui, X He - Future Generation Computer Systems, 2024 - Elsevier
With the continuous popularization and evolution of 5G and 6G, mobile edge computing has
achieved rapid development. This study explores the New Generation Mobile Edge …
achieved rapid development. This study explores the New Generation Mobile Edge …
[PDF][PDF] 面向绿色计算的车辆协同任务卸载方法
张红霞， 吕智豪， 席诗语， 刘佳敏， 郭加树， 张培颖 - 电子与信息学报, 2024 - jeit.ac.cn
车辆边缘计算(VEC) 为处理计算密集, 延迟敏感型任务提供了新的范式, 然而边缘服务器在整合
可再生能源方面的能力较差. 因此, 为了提高边缘服务器的能效, 该文设计了一种面向绿色计算的 …
可再生能源方面的能力较差. 因此, 为了提高边缘服务器的能效, 该文设计了一种面向绿色计算的 …