[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 …

Task scheduling in cloud computing based on meta-heuristics: review, taxonomy, open challenges, and future trends

EH Houssein, AG Gad, YM Wazery… - Swarm and Evolutionary …, 2021 - Elsevier
Cloud computing is a recently looming-evoked paradigm, the aim of which is to provide on-
demand, pay-as-you-go, internet-based access to shared computing resources (hardware …

Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges

SS Gill, S Tuli, M Xu, I Singh, KV Singh, D Lindsay… - Internet of Things, 2019 - Elsevier
Cloud computing plays a critical role in modern society and enables a range of applications
from infrastructure to social media. Such system must cope with varying load and evolving …

Using the internet of things in smart energy systems and networks

T Ahmad, D Zhang - Sustainable Cities and Society, 2021 - Elsevier
Private businesses and policymakers are accelerating the deployment and advancement of
smart grid technology innovations that can support smart energy systems. Technological …

A comprehensive survey for scheduling techniques in cloud computing

M Kumar, SC Sharma, A Goel, SP Singh - Journal of Network and …, 2019 - Elsevier
Resource scheduling becomes the prominent issue in cloud computing due to rapid growth
of on demand request and heterogeneous nature of cloud resources. Cloud provides …

Performance evaluation metrics for cloud, fog and edge computing: A review, taxonomy, benchmarks and standards for future research

MS Aslanpour, SS Gill, AN Toosi - Internet of Things, 2020 - Elsevier
Optimization is an inseparable part of Cloud computing, particularly with the emergence of
Fog and Edge paradigms. Not only these emerging paradigms demand reevaluating cloud …

Scheduling in cloud manufacturing: state-of-the-art and research challenges

Y Liu, L Wang, XV Wang, X Xu… - International Journal of …, 2019 - Taylor & Francis
For the past eight years, cloud manufacturing as a new manufacturing paradigm has
attracted a large amount of research interest worldwide. The aim of cloud manufacturing is to …

Resource allocation and service provisioning in multi-agent cloud robotics: A comprehensive survey

M Afrin, J **, A Rahman, A Rahman… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Robotic applications nowadays are widely adopted to enhance operational automation and
performance of real-world Cyber-Physical Systems (CPSs) including Industry 4.0 …

IoT and fog-computing-based predictive maintenance model for effective asset management in Industry 4.0 using machine learning

YK Teoh, SS Gill, AK Parlikad - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
The assets in Industry 4.0 are categorized into physical, virtual, and human. The innovation
and popularization of ubiquitous computing enhance the usage of smart devices: RFID tags …

Q-learning based dynamic task scheduling for energy-efficient cloud computing

D Ding, X Fan, Y Zhao, K Kang, Q Yin, J Zeng - Future Generation …, 2020 - Elsevier
High energy consumption has become a growing concern in the operation of complex cloud
data centers due to the ever-expanding size of cloud computing facilities and the ever …