An efficient task scheduling in fog computing using improved artificial hummingbird algorithm

R Ghafari, N Mansouri - Journal of Computational Science, 2023 - Elsevier
IoT edge devices have become more popular due to the rapid growth in IoT applications in
recent years. Task scheduling reduces latency and application computation times, while …

Improved Black Widow Optimization: An investigation into enhancing cloud task scheduling efficiency

MA Abu-Hashem, M Shehab, MKY Shambour… - … Informatics and Systems, 2024 - Elsevier
Abstract The Black Widow Optimization (BWO) algorithm has garnered significant attention
within the realm of metaheuristic algorithms due to its potential to address diverse problems …

[HTML][HTML] Research on patent quality evaluation based on rough set and cloud model

L Zhang, T Zhang, Y Lang, J Li, F Ji - Expert Systems with Applications, 2024 - Elsevier
The evaluation and identification of high-quality patents are urgently needed for the
technological research and development and the transformation of achievements …

[HTML][HTML] Energy-optimal DNN model placement in UAV-enabled edge computing networks

J Tang, G Wu, MM Jalalzai, L Wang, B Zhang… - Digital Communications …, 2023 - Elsevier
Unmanned aerial vehicle (UAV)-enabled edge computing is emerging as a potential
enabler for Artificial Intelligence of Things (AIoT) in the forthcoming sixth-generation (6G) …

ECDX: Energy consumption prediction model based on distance correlation and XGBoost for edge data center

C Li, D Zhu, C Hu, X Li, S Nan, H Huang - Information Sciences, 2023 - Elsevier
The rapid development of artificial intelligence (AI) and edge computing technology has
promoted the rapid growth of the number of data centers, but also caused large energy …

Qdrl: Queue-aware online drl for computation offloading in industrial internet of things

A Xu, Z Hu, X Zhang, H Xiao, H Zheng… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Recently, the Industrial Internet of Things (IIoT) has shown great application value in
environmental monitoring. However, it suffers from serious bottlenecks in energy and …

[HTML][HTML] A hybrid deep learning model using CNN and K-Mean clustering for energy efficient modelling in mobile EdgeIoT

D Bisen, UK Lilhore, P Manoharan, F Dahan… - Electronics, 2023 - mdpi.com
In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can
perform in limited energy by selecting the best communication path and components. This …

Energy-stabilized computing offloading algorithm for uavs with energy harvesting

K Zeng, X Li, T Shen - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Recent research on unmanned aerial vehicle-based (UAV) computational offloading
algorithms has employed energy harvesting mechanisms to improve the efficiency of edge …

A cost‐efficient and QoS‐aware adaptive placement of applications in fog computing

H Li, C Xu, T Wang, J Wang, P Zheng… - Concurrency and …, 2023 - Wiley Online Library
With the rapid development of the Internet of Things (IoT), fog computing has emerged as a
complementary solution to address the issues faced in cloud computing. However, it is a …

Real-time three-level energy management strategy for series hybrid wheel loaders based on WG-MPC

R Gao, G Zhou, Q Wang - Energy, 2024 - Elsevier
Abstract The application of Hybrid Electric Wheel Loaders (HEWL) represents an attractive
option for future industrial development. In order to reduce the equivalent fuel consumption …