Resource scheduling in edge computing: A survey

Q Luo, S Hu, C Li, G Li, W Shi - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless
networks, the surging demand for data communications and computing calls for the …

AI for next generation computing: Emerging trends and future directions

SS Gill, M Xu, C Ottaviani, P Patros, R Bahsoon… - Internet of Things, 2022 - Elsevier
Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

Federated learning with differential privacy: Algorithms and performance analysis

K Wei, J Li, M Ding, C Ma, HH Yang… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Federated learning (FL), as a type of distributed machine learning, is capable of significantly
preserving clients' private data from being exposed to adversaries. Nevertheless, private …

Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for cps

FO Olowononi, DB Rawat, C Liu - … Communications Surveys & …, 2020 - ieeexplore.ieee.org
Cyber Physical Systems (CPS) are characterized by their ability to integrate the physical and
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …

Reducing offloading latency for digital twin edge networks in 6G

W Sun, H Zhang, R Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
6G is envisioned to empower wireless communication and computation through the
digitalization and connectivity of everything, by establishing a digital representation of the …

A survey on deep transfer learning to edge computing for mitigating the COVID-19 pandemic

A Sufian, A Ghosh, AS Sadiq… - Journal of Systems …, 2020 - Elsevier
Global Health sometimes faces pandemics as are currently facing COVID-19 disease. The
spreading and infection factors of this disease are very high. A huge number of people from …

Adaptive federated learning and digital twin for industrial internet of things

W Sun, S Lei, L Wang, Z Liu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Industrial Internet of Things (IoT) enables distributed intelligent services varying with the
dynamic and realtime industrial environment to achieve Industry 4.0 benefits. In this article …

Cloud-edge orchestration for the Internet of Things: Architecture and AI-powered data processing

Y Wu - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) has been deeply penetrated into a wide range of important and
critical sectors, including smart city, water, transportation, manufacturing, and smart factory …

Joint resource allocation and incentive design for blockchain-based mobile edge computing

W Sun, J Liu, Y Yue, P Wang - IEEE transactions on wireless …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC), as a promising technology, provides proximate and prompt
computing service for mobile users on various applications. With appropriate incentives …

Deep reinforcement learning based resource management for DNN inference in industrial IoT

W Zhang, D Yang, H Peng, W Wu… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Performing deep neural network (DNN) inference in real time requires excessive network
resources, which poses a big challenge to the resource-limited industrial Internet of things …