A survey on end-edge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet

J Ren, D Zhang, S He, Y Zhang, T Li - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Sending data to the cloud for analysis was a prominent trend during the past decades,
driving cloud computing as a dominant computing paradigm. However, the dramatically …

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 …

Mobility-aware multi-hop task offloading for autonomous driving in vehicular edge computing and networks

L Liu, M Zhao, M Yu, MA Jan, D Lan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) has gained increasing interest due to its potential to
provide low latency and reduce the load in backhaul networks. In order to meet drastically …

The convergence and interplay of edge, fog, and cloud in the AI-driven Internet of Things (IoT)

F Firouzi, B Farahani, A Marinšek - Information Systems, 2022 - Elsevier
Abstract The Internet of Things (IoT) tsunami, public embracement, and the ubiquitous
adoption of smart devices are affecting virtually every industry, directly or indirectly. The …

Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing

H Zhou, K Jiang, X Liu, X Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …

Toward edge intelligence: Multiaccess edge computing for 5G and Internet of Things

Y Liu, M Peng, G Shou, Y Chen… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
To satisfy the increasing demand of mobile data traffic and meet the stringent requirements
of the emerging Internet-of-Things (IoT) applications such as smart city, healthcare, and …

Deep reinforcement learning for offloading and resource allocation in vehicle edge computing and networks

Y Liu, H Yu, S Xie, Y Zhang - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is a promising technology to extend the diverse services to
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …

Managing healthcare supply chain through artificial intelligence (AI): A study of critical success factors

A Kumar, V Mani, V Jain, H Gupta… - Computers & Industrial …, 2023 - Elsevier
Healthcare is one of the most critical sectors due to its importance in handling public health.
With the outbreak of various diseases, more recently during Covid-19, this sector has gained …

Deep reinforcement learning for stochastic computation offloading in digital twin networks

Y Dai, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The rapid development of industrial Internet of Things (IIoT) requires industrial production
towards digitalization to improve network efficiency. Digital Twin is a promising technology to …

Edge-computing-enabled smart cities: A comprehensive survey

LU Khan, I Yaqoob, NH Tran… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Recent years have disclosed a remarkable proliferation of compute-intensive applications in
smart cities. Such applications continuously generate enormous amounts of data which …