LsiA3CS: Deep Reinforcement Learning-Based Cloud-Edge Collaborative Task Scheduling in Large-Scale IIoT

Z Zhang, F Zhang, Z Xiong, K Zhang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Task scheduling in large-scale industrial Internet of Things (IIoT) is characterized by the
presence of diverse resources and the requirement for efficient and synchronized …

A review of privacy and security of edge computing in smart healthcare systems: issues, challenges, and research directions

A Alzu'bi, A Alomar, S Alkhaza'leh… - Tsinghua Science …, 2024 - ieeexplore.ieee.org
The healthcare industry is rapidly adapting to new computing environments and
technologies. With academics increasingly committed to developing and enhancing …

Implications of edge computing for static site generation

J Vepsäläinen, A Hellas, P Vuorimaa - arXiv preprint arXiv:2309.05669, 2023 - arxiv.org
Static site generation (SSG) is a common technique in the web development space to create
performant websites that are easy to host. Numerous SSG tools exist, and the approach has …

[HTML][HTML] Network-assisted processing of advanced IoT applications: challenges and proof-of-concept application

H Mora, FA Pujol, T Ramírez, A Jimeno-Morenilla… - Cluster …, 2024 - Springer
Recent advances in the area of the Internet of Things shows that devices are usually
resource-constrained. To enable advanced applications on these devices, it is necessary to …

Internet of everything: Applications, and security challenges

M Sajid, A Harris, S Habib - 2021 International conference on …, 2021 - ieeexplore.ieee.org
The field of Internet of Everything (IoE) is based upon four pillars namely data, processes,
people and things. IoE vows to mainly change over how we work, live, and interact, and it …

A semantic web approach to fault tolerant autonomous manufacturing

F El Kalach, R Wickramarachchi, R Harik… - IEEE Intelligent …, 2023 - ieeexplore.ieee.org
The next phase of manufacturing is centered on making the switch from traditional
automated to autonomous systems. Future factories are required to be agile, allowing for …

Adapting Kubernetes controllers to the edge: on-demand control planes using Wasm and WASI

M Sebrechts, T Ramlot, S Borny… - 2022 IEEE 11th …, 2022 - ieeexplore.ieee.org
Kubernetes' high resource requirements hamper its adoption in constrained environments
such as the edge and fog. Its extensible control plane is a significant contributor to this …

The use of edge computing-based internet of things big data in the design of power intelligent management and control platform

X Ju, R Gou, Y Xiao, Z Wang… - International journal of …, 2022 - inderscienceonline.com
The purpose of this research is to apply the Internet of Things (IoT) and big data technology
to the power management and control platform, and improve the intelligent level of power …

[PDF][PDF] A novel distributed machine learning model to detect attacks on edge computing network

TM Hoang, TL Le Thi, NM Quy - Journal of Advances in Information …, 2023 - jait.us
To meet the growing number and variety of IoT devices in 5G and 6G network environments,
the development of edge computing technology is a powerful strategy for offloading …

Enabling microservices management for Deep Learning applications across the Edge-Cloud Continuum

Z Houmani, D Balouek-Thomert… - 2021 IEEE 33rd …, 2021 - ieeexplore.ieee.org
Deep Learning has shifted the focus of traditional batch workflows to data-driven feature
engineering on streaming data. In particular, the execution of Deep Learning workflows …