Navigating industry 5.0: A survey of key enabling technologies, trends, challenges, and opportunities
This century has been a major avenue for revolutionary changes in technology and industry.
Industries have transitioned towards intelligent automation, relying less on human …
Industries have transitioned towards intelligent automation, relying less on human …
Edge computing for industry 5.0: fundamental, applications and research challenges
Industry 5.0 is the next stage in industrial evolution, collaborating between human ingenuity
and intelligent technologies to provide manufacturing solutions. Integrating modern …
and intelligent technologies to provide manufacturing solutions. Integrating modern …
[HTML][HTML] Secure-fault-tolerant efficient industrial internet of healthcare things framework based on digital twin federated fog-cloud networks
Abstract The Industrial Internet of Healthcare Things (IIoHT) is the emerging paradigm in
digital healthcare. Context-aware healthcare sensors, local intelligent watches, healthcare …
digital healthcare. Context-aware healthcare sensors, local intelligent watches, healthcare …
Deep reinforcement learning for RIS-aided secure mobile edge computing in industrial internet of things
J Xu, A Xu, L Chen, Y Chen, X Liang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) has been regarded as a promising paradigm to support the
compute-intensive and delay-sensitive industrial Internet of things (IIoT) applications …
compute-intensive and delay-sensitive industrial Internet of things (IIoT) applications …
Towards a New Paradigm for Digital Health Training and Education in Australia: Exploring the Implication of the Fifth Industrial Revolution
Featured Application This paper presents a new, fifth industrial revolution (Industry 5.0)-
inspired paradigm for educating and training Australian healthcare professionals and …
inspired paradigm for educating and training Australian healthcare professionals and …
Building trusted federated learning: Key technologies and challenges
Federated learning (FL) provides convenience for cross-domain machine learning
applications and has been widely studied. However, the original FL is still vulnerable to …
applications and has been widely studied. However, the original FL is still vulnerable to …
Federated learning for green and sustainable 6G IIoT applications
The 6th generation mobile network (6G) is expected to be launched in the early 2030s. The
architecture of 6G will be the convergence of space, air, ground, and undersea networks …
architecture of 6G will be the convergence of space, air, ground, and undersea networks …
Robust risk-sensitive task offloading for edge-enabled industrial Internet of Things
Edge-enabled Industrial Internet of Things (E-IIoT) has gained massive attention as a new
type of IIoT for hosting emerging low-latency applications. However, due to device variations …
type of IIoT for hosting emerging low-latency applications. However, due to device variations …
Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …
An efficient combination of genetic algorithm and particle swarm optimization for scheduling data-intensive tasks in heterogeneous cloud computing
K Shao, H Fu, B Wang - Electronics, 2023 - mdpi.com
Task scheduling is still an open issue for improving the performance of cloud services.
Focusing on addressing the issue, we first formulate the task-scheduling problem of …
Focusing on addressing the issue, we first formulate the task-scheduling problem of …