Applying machine learning techniques for caching in next-generation edge networks: A comprehensive survey

J Shuja, K Bilal, W Alasmary, H Sinky… - Journal of Network and …, 2021 - Elsevier
Edge networking is a complex and dynamic computing paradigm that aims to push cloud re-
sources closer to the end user improving responsiveness and reducing backhaul traffic …

Joint wireless power transfer and task offloading in mobile edge computing: a survey

E Mustafa, J Shuja, SK uz Zaman, AI Jehangiri, S Din… - Cluster …, 2022 - Springer
The promising technique of Wireless Power Transfer (WPT) to end devices and sensors has
gained the attention of researchers recently. Mobile edge computing (MEC) is also …

Towards effective offloading mechanisms in fog computing

M Sheikh Sofla, M Haghi Kashani, E Mahdipour… - Multimedia Tools and …, 2022 - Springer
Fog computing is considered a formidable next-generation complement to cloud computing.
Nowadays, in light of the dramatic rise in the number of IoT devices, several problems have …

Reinforcement learning for intelligent online computation offloading in wireless powered edge networks

E Mustafa, J Shuja, K Bilal, S Mustafa, T Maqsood… - Cluster …, 2023 - Springer
The method of charging mobile devices with wireless power transfer (WPT) from the base
station (BS) integrated with mobile edge computing (MEC) increases the potential of MEC …

Applying machine learning techniques for caching in edge networks: A comprehensive survey

J Shuja, K Bilal, W Alasmary, H Sinky… - arxiv preprint arxiv …, 2020 - arxiv.org
Edge networking is a complex and dynamic computing paradigm that aims to push cloud
resources closer to the end user improving responsiveness and reducing backhaul traffic …

Cognitive data offloading in mobile edge computing for internet of things

PA Apostolopoulos, EE Tsiropoulou… - IEEE …, 2020 - ieeexplore.ieee.org
Data offloading to Mobile Edge Computing (MEC) servers is an attractive choice for resource-
constrained Internet of Things (IoT) devices, towards reducing their computational effort. In …

Task scheduling for smart city applications based on multi-server mobile edge computing

Y Deng, Z Chen, X Yao, S Hassan, J Wu - IEEE Access, 2019 - ieeexplore.ieee.org
The smart city is increasingly gaining worldwide attention. It has the potential to improve the
quality of life in convenience, at work, and in safety, among many others' utilizations …

Optimized task allocation for IoT application in mobile-edge computing

J Liu, C Liu, B Wang, G Gao… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the rapid upgrading and explosive growth of Internet of Things (IoT) devices in mobile-
edge computing, more and more IoT applications with high resource requirements are …

Gradient scheduling with global momentum for asynchronous federated learning in edge environment

H Wang, R Li, C Li, P Zhou, Y Li… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Federated Learning has attracted widespread attention in recent years because it allows
massive edge nodes to collaboratively train machine learning models without sharing their …

A mobile edge-based crowdsensing framework for heterogeneous iot

H Lamaazi, R Mizouni, S Singh, H Otrok - IEEE Access, 2020 - ieeexplore.ieee.org
In this article, we consider the problem of distributed offloading in mobile crowdsensing
(MCS) by the means of mobile edge computing (MEC). Deploying MEC in MCS can help …