[HTML][HTML] Internet of things: a comprehensive overview on protocols, architectures, technologies, simulation tools, and future directions

M Mansour, A Gamal, AI Ahmed, LA Said, A Elbaz… - Energies, 2023 - mdpi.com
The Internet of Things (IoT) is a global network of interconnected computing, sensing, and
networking devices that can exchange data and information via various network protocols. It …

[HTML][HTML] Graph neural networks for intelligent modelling in network management and orchestration: a survey on communications

P Tam, I Song, S Kang, S Ros, S Kim - Electronics, 2022 - mdpi.com
The advancing applications based on machine learning and deep learning in
communication networks have been exponentially increasing in the system architectures of …

Adaptive federated deep reinforcement learning for proactive content caching in edge computing

D Qiao, S Guo, D Liu, S Long… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the aggravation of data explosion and backhaul loads on 5 G edge network, it is difficult
for traditional centralized cloud to meet the low latency requirements for content access. The …

Dependent tasks offloading in mobile edge computing: a multi-objective evolutionary optimization strategy

Y Gong, K Bian, F Hao, Y Sun, Y Wu - Future Generation Computer Systems, 2023 - Elsevier
Due to the proliferation of applications such as virtual reality and online games with high real-
time requirements, Mobile Edge Computing (MEC) has become a promising computing …

Joint device association, resource allocation, and computation offloading in ultradense multidevice and multitask IoT networks

T Zhou, Y Yue, D Qin, X Nie, X Li… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
With the emergence of more and more applications of Internet of Things (IoT) mobile devices
(IMDs), a contradiction between mobile energy demand and limited battery capacity …

Collaborative cloud-edge-end task offloading with task dependency based on deep reinforcement learning

T Tang, C Li, F Liu - Computer Communications, 2023 - Elsevier
With the explosive growth of the Internet of Things (IoT), IoT devices generate massive
amounts of data and demand, which poses a huge challenge to IoT devices with limited …

TMHD: Twin-Bridge Scheduling of Multi-Heterogeneous Dependent Tasks for Edge Computing

W Liang, J Xiao, Y Chen, C Yang, K Xie, KC Li… - Future Generation …, 2024 - Elsevier
As an efficient computing paradigm, Mobile Edge Computing (MEC) is essential in assisting
mobile devices with real-time complex tasks such as big data analytics. In MEC, application …

Intelligent energy-efficient scheduling with ant colony techniques for heterogeneous edge computing

J Liu, P Yang, C Chen - Journal of Parallel and Distributed Computing, 2023 - Elsevier
Energy efficiency is a significant issue in heterogeneous edge computing systems for a large
number of latency-sensitive applications. This article presents an efficient technique to …

[HTML][HTML] Task-offloading strategy based on performance prediction in vehicular edge computing

F Zeng, J Tang, C Liu, X Deng, W Li - Mathematics, 2022 - mdpi.com
In vehicular edge computing, network performance and computing resources dynamically
change, and vehicles should find the optimal strategy for offloading their tasks to servers to …

Secure and multi-step computation offloading and resource allocation in ultra-dense multi-task NOMA-enabled IoT networks

T Zhou, Y Fu, D Qin, X Nie, N Jiang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Ultradense networks are widely regarded as a promising solution to explosively growing
applications of Internet of Things (IoT) mobile devices (IMDs). However, complicated and …