A survey on the computation offloading approaches in mobile edge computing: A machine learning-based perspective

A Shakarami, M Ghobaei-Arani, A Shahidinejad - Computer Networks, 2020 - Elsevier
With the rapid developments in emerging mobile technologies, utilizing resource-hungry
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …

Scheduling IoT applications in edge and fog computing environments: a taxonomy and future directions

M Goudarzi, M Palaniswami, R Buyya - ACM Computing Surveys, 2022 - dl.acm.org
Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the
network with low latency and high-access bandwidth to support a diverse range of IoT …

An application placement technique for concurrent IoT applications in edge and fog computing environments

M Goudarzi, H Wu, M Palaniswami… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Fog/Edge computing emerges as a novel computing paradigm that harnesses resources in
the proximity of the Internet of Things (IoT) devices so that, alongside with the cloud servers …

Secure and optimized load balancing for multitier IoT and edge-cloud computing systems

WZ Zhang, IA Elgendy, M Hammad… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Mobile-edge computing (MEC) has emerged as a new computing paradigm with great
potential to alleviate resource limitations attributed to mobile device users (MDUs) by …

Efficient and secure multi-user multi-task computation offloading for mobile-edge computing in mobile IoT networks

IA Elgendy, WZ Zhang, Y Zeng, H He… - … on Network and …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a new paradigm to alleviate resource limitations of mobile
IoT networks through computation offloading with low latency. This article presents an …

Data augmentation for deep learning-based radio modulation classification

L Huang, W Pan, Y Zhang, L Qian, N Gao, Y Wu - IEEE access, 2019 - ieeexplore.ieee.org
Deep learning has recently been applied to automatically classify the modulation categories
of received radio signals without manual experience. However, training deep learning …

Advanced deep learning-based computational offloading for multilevel vehicular edge-cloud computing networks

M Khayyat, IA Elgendy, A Muthanna… - IEEE …, 2020 - ieeexplore.ieee.org
The promise of low latency connectivity and efficient bandwidth utilization has driven the
recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC) …

Intelligent computation offloading and resource allocation in IIoT with end-edge-cloud computing using NSGA-III

K Peng, H Huang, B Zhao, A Jolfaei… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT), which consists of massive IoT devices and industrial
infrastructures such as wireless access points to acquire intelligent services, has been …

Meeting the requirements of internet of things: The promise of edge computing

A Hazra, A Kalita, M Gurusamy - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Over the last few decades, Internet of Things (IoT) has become the spotlight area of research
within the Industries and Academics. Primarily, IoT devices are characterized by small and …

Intelligent resource allocation for edge-cloud collaborative networks: A hybrid DDPG-D3QN approach

H Hu, D Wu, F Zhou, X Zhu, RQ Hu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
To handle the ever-increasing IoT devices with computation-intensive and delay-critical
applications, it is imperative to leverage the collaborative potential of edge and cloud …