[HTML][HTML] Edge AI: a survey

R Singh, SS Gill - Internet of Things and Cyber-Physical Systems, 2023 - Elsevier
Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …

AI-based fog and edge computing: A systematic review, taxonomy and future directions

S Iftikhar, SS Gill, C Song, M Xu, MS Aslanpour… - Internet of Things, 2023 - Elsevier
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …

[HTML][HTML] Modern computing: Vision and challenges

SS Gill, H Wu, P Patros, C Ottaviani, P Arora… - … and Informatics Reports, 2024 - Elsevier
Over the past six decades, the computing systems field has experienced significant
transformations, profoundly impacting society with transformational developments, such as …

Edge learning for 6G-enabled Internet of Things: A comprehensive survey of vulnerabilities, datasets, and defenses

MA Ferrag, O Friha, B Kantarci… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The deployment of the fifth-generation (5G) wireless networks in Internet of Everything (IoE)
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …

A comprehensive review of AI techniques for resource management in fog computing: Trends, challenges and future directions

D Alsadie - IEEE Access, 2024 - ieeexplore.ieee.org
Fog computing (FC), extending cloud services to the network edge, has emerged as a key
paradigm for low-latency applications like the Internet of Things (IoT). However, efficient …

[HTML][HTML] A comprehensive survey of energy-efficient computing to enable sustainable massive IoT networks

MH Alsharif, AH Kelechi, A Jahid… - Alexandria Engineering …, 2024 - Elsevier
Energy efficiency is a key area of research aimed at achieving sustainable and
environmentally friendly networks. With the rise in data traffic and network congestion, IoT …

A predictive energy-aware scheduling strategy for scientific workflows in fog computing

M Nazeri, M Soltanaghaei, R Khorsand - Expert Systems with Applications, 2024 - Elsevier
Fog computing paradigm provides diverse processing resources and storage close to the
edge of Internet of Things (IoT) networks. Workflow scheduling is an open issue in fog …

An energy-efficient and deadline-aware workflow scheduling algorithm in the fog and cloud environment

N Khaledian, K Khamforoosh, R Akraminejad… - computing, 2024 - Springer
Abstract The Internet of Things (IoT) is constantly evolving. The variety of IoT applications
has caused new demands to emerge on users' part and competition between computing …

An energy aware resource allocation based on combination of CNN and GRU for virtual machine selection

Z Khodaverdian, H Sadr, SA Edalatpanah… - Multimedia tools and …, 2024 - Springer
The use of cloud computing service models is rapidly increasing, but inefficient resource
usage in cloud data centers can lead to great energy consumption and costs. To address …

An optimal scheduling method in IoT-fog-cloud network using combination of Aquila optimizer and African vultures optimization

Q Liu, H Kosarirad, S Meisami, KA Alnowibet… - Processes, 2023 - mdpi.com
Today, fog and cloud computing environments can be used to further develop the Internet of
Things (IoT). In such environments, task scheduling is very efficient for executing user …