Hardware-assisted machine learning in resource-constrained IoT environments for security: review and future prospective

G Kornaros - IEEE Access, 2022 - ieeexplore.ieee.org
As the Internet of Things (IoT) technology advances, billions of multidisciplinary smart
devices act in concert, rarely requiring human intervention, posing significant challenges in …

Big data resource management & networks: Taxonomy, survey, and future directions

FM Awaysheh, M Alazab, S Garg… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Big Data (BD) platforms have a long tradition of leveraging trends and technologies from the
broader computer network and communication community. For several years, dedicated …

Optimizing federated learning in distributed industrial IoT: A multi-agent approach

W Zhang, D Yang, W Wu, H Peng… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
In this paper, we aim to make the best joint decision of device selection and computing and
spectrum resource allocation for optimizing federated learning (FL) performance in …

Edge intelligence: The confluence of edge computing and artificial intelligence

S Deng, H Zhao, W Fang, J Yin… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Along with the rapid developments in communication technologies and the surge in the use
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …

Com-DDPG: Task offloading based on multiagent reinforcement learning for information-communication-enhanced mobile edge computing in the internet of vehicles

H Gao, X Wang, W Wei, A Al-Dulaimi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The emergence of the Internet of Vehicles (IoV) introduces challenges regarding
computation-intensive and time-sensitive related services for data processing and …

Collaborative learning-based industrial IoT API recommendation for software-defined devices: the implicit knowledge discovery perspective

H Gao, X Qin, RJD Barroso, W Hussain… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The industrial Internet of things (IIoT), a new computing mode in Industry 4.0, is deployed to
connect IoT devices and use communication technology to respond to control commands …

Auditing cache data integrity in the edge computing environment

B Li, Q He, F Chen, H **, Y **ang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Edge computing allows app vendors to deploy their applications and relevant data on
distributed edge servers to serve nearby users. Caching data on edge servers can minimize …

QoS prediction for service recommendation with features learning in mobile edge computing environment

Y Yin, Z Cao, Y Xu, H Gao, R Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In recent years, deep neural networks have achieved exciting results in a variety of tasks,
and many fields try to introduce neural network techniques. In mobile edge computing, there …

Distributed redundant placement for microservice-based applications at the edge

H Zhao, S Deng, Z Liu, J Yin… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Multi-access edge computing (MEC) is booming as a promising paradigm to push the
computation and communication resources from cloud to the network edge to provide …

Dynamic bargain game theory in the internet of things for data trustworthiness

AC Sumathi, M Akila, R Pérez de Prado, M Wozniak… - Sensors, 2021 - mdpi.com
Smart home and smart building systems based on the Internet of Things (IoT) in smart cities
currently suffer from security issues. In particular, data trustworthiness and efficiency are two …