MR-DRO: A fast and efficient task offloading algorithm in heterogeneous edge/cloud computing environments

Z Zhang, N Wang, H Wu, C Tang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the rapid development of Internet of Things (IoT) and next-generation communication
technologies, resource-constrained mobile devices (MDs) fail to meet the demand of …

DMRO: A deep meta reinforcement learning-based task offloading framework for edge-cloud computing

G Qu, H Wu, R Li, P Jiao - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
With the explosive growth of mobile data and the unprecedented demand for computing
power, resource-constrained edge devices cannot effectively meet the requirements of …

Collaborative cloud-edge-end task offloading with task dependency based on deep reinforcement learning

T Tang, C Li, F Liu - Computer Communications, 2023 - Elsevier
With the explosive growth of the Internet of Things (IoT), IoT devices generate massive
amounts of data and demand, which poses a huge challenge to IoT devices with limited …

Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions

MY Akhlaqi, ZBM Hanapi - Journal of Network and Computer Applications, 2023 - Elsevier
Many enterprise companies migrate their services and applications to the cloud to benefit
from cloud computing advantages. Meanwhile, the rapidly increasing number of connected …

DECO: A deadline-aware and energy-efficient algorithm for task offloading in mobile edge computing

S Azizi, M Othman, H Khamfroush - IEEE Systems Journal, 2022 - ieeexplore.ieee.org
With the rapid development in the area of Internet of Things (IoT), the number of delay-
sensitive and power-hungry IoT applications has drastically increased over the past few …

Real-time offloading for dependent and parallel tasks in cloud-edge environments using deep reinforcement learning

X Chen, S Hu, C Yu, Z Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As an effective technique to relieve the problem of resource constraints on mobile devices
(MDs), the computation offloading utilizes powerful cloud and edge resources to process the …

Optimized multi-user dependent tasks offloading in edge-cloud computing using refined whale optimization algorithm

KM Hosny, AI Awad, MM Khashaba… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Despite the extensive use of IoT and mobile devices in the different applications, their
computing power, memory, and battery life are still limited. Multi-Access Edge Computing …

Collaborate edge and cloud computing with distributed deep learning for smart city internet of things

H Wu, Z Zhang, C Guan, K Wolter… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
City Internet-of-Things (IoT) applications are becoming increasingly complicated and thus
require large amounts of computational resources and strict latency requirements. Mobile …

A novel framework for mobile-edge computing by optimizing task offloading

A Naouri, H Wu, NA Nouri, S Dhelim… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the emergence of mobile computing offloading paradigms, such as mobile-edge
computing (MEC), many Internet of Things applications can take advantage of the computing …

A survey and taxonomy on task offloading for edge-cloud computing

B Wang, C Wang, W Huang, Y Song, X Qin - IEEE Access, 2020 - ieeexplore.ieee.org
Edge-cloud computing, combining the benefits of both edge computing and cloud
computing, is one of the most promising ways to address the resource insufficiency of smart …