Resource scheduling in edge computing: A survey

Q Luo, S Hu, C Li, G Li, W Shi - IEEE communications surveys & …, 2021 - ieeexplore.ieee.org
With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless
networks, the surging demand for data communications and computing calls for the …

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 …

Intelligent delay-aware partial computing task offloading for multiuser industrial Internet of Things through edge computing

X Deng, J Yin, P Guan, NN **ong… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The development of Industrial Internet of Things (IIoT) and Industry 4.0 has completely
changed the traditional manufacturing industry. Intelligent IIoT technology usually involves a …

Privacy-preserving offloading scheme in multi-access mobile edge computing based on MADRL

G Wu, X Chen, Z Gao, H Zhang, S Yu, S Shen - Journal of Parallel and …, 2024 - Elsevier
With the development of industrialization and intelligence, the Industrial Internet of Things
(IIoT) has gradually become the direction for traditional industries to transform into modern …

PPO2: Location privacy-oriented task offloading to edge computing using reinforcement learning for intelligent autonomous transport systems

H Gao, W Huang, T Liu, Y Yin… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
AI-empowered 5G/6G networks play a substantial role in taking full advantage of the Internet
of Things (IoT) to perform complex computing by offloading tasks to edge services deployed …

Ai-based mobile edge computing for iot: Applications, challenges, and future scope

A Singh, SC Satapathy, A Roy, A Gutub - Arabian Journal for Science and …, 2022 - Springer
New technology is needed to meet the latency and bandwidth issues present in cloud
computing architecture specially to support the currency of 5G networks. Accordingly, mobile …

Collaborative service placement, task scheduling, and resource allocation for task offloading with edge-cloud cooperation

W Fan, L Zhao, X Liu, Y Su, S Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In an edge-cloud cooperative computing network, the task offloading performance can be
further improved by the edge-cloud and edge-edge cooperation, in which the tasks can be …

Edge intelligence: Federated learning-based privacy protection framework for smart healthcare systems

M Akter, N Moustafa, T Lynar… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Federated learning methods offer secured monitor services and privacy-preserving
paradigms to end-users and organisations in the Internet of Things networks such as smart …

Diagnosis of skin diseases in the era of deep learning and mobile technology

E Goceri - Computers in Biology and Medicine, 2021 - Elsevier
Efficient methods developed with deep learning in the last ten years have provided
objectivity and high accuracy in the diagnosis of skin diseases. They also support accurate …

IoMT-enabled real-time blood glucose prediction with deep learning and edge computing

T Zhu, L Kuang, J Daniels, P Herrero… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Blood glucose (BG) prediction is essential to the success of glycemic control in type 1
diabetes (T1D) management. Empowered by the recent development of the Internet of …