A review on the edge caching mechanisms in the mobile edge computing: A social-aware perspective

M Reiss-Mirzaei, M Ghobaei-Arani, L Esmaeili - Internet of Things, 2023 - Elsevier
In recent years, we have witnessed the rapid development of the 5G technology, the
computing capabilities of smartphones, and the use of these technologies and types of smart …

Transfer learning for wireless networks: A comprehensive survey

CT Nguyen, N Van Huynh, NH Chu… - Proceedings of the …, 2022 - ieeexplore.ieee.org
With outstanding features, machine learning (ML) has become the backbone of numerous
applications in wireless networks. However, the conventional ML approaches face many …

Mobility-aware computational offloading in mobile edge networks: a survey

SK Zaman, AI Jehangiri, T Maqsood, Z Ahmad… - Cluster …, 2021 - Springer
Technological evolution of mobile devices, such as smart phones, laptops, wearable and
other handheld devices have come up with the emergence of different user applications in …

LiMPO: Lightweight mobility prediction and offloading framework using machine learning for mobile edge computing

SK Zaman, AI Jehangiri, T Maqsood, N Haq, AI Umar… - Cluster …, 2023 - Springer
Several applications have emerged with the proliferation of mobile devices to provide
communication, learning, social networking, entertainment, and community computing …

Joint wireless power transfer and task offloading in mobile edge computing: a survey

E Mustafa, J Shuja, SK uz Zaman, AI Jehangiri, S Din… - Cluster …, 2022 - Springer
The promising technique of Wireless Power Transfer (WPT) to end devices and sensors has
gained the attention of researchers recently. Mobile edge computing (MEC) is also …

Edge-cloud polarization and collaboration: A comprehensive survey for ai

J Yao, S Zhang, Y Yao, F Wang, J Ma… - … on Knowledge and …, 2022 - ieeexplore.ieee.org
Influenced by the great success of deep learning via cloud computing and the rapid
development of edge chips, research in artificial intelligence (AI) has shifted to both of the …

Extreme learning machine for plant diseases classification: a sustainable approach for smart agriculture

D Aqel, S Al-Zubi, A Mughaid, Y Jararweh - Cluster Computing, 2022 - Springer
Nowadays, the economy of countries highly depends on the agriculture productivity which
has a great effect on the development of human civilization. Sometimes, plant diseases …

Container placement and migration in edge computing: Concept and scheduling models

O Oleghe - IEEE Access, 2021 - ieeexplore.ieee.org
Containers are a form of software virtualization, rapidly becoming the de facto way of
providing edge computing services. Research on container-based edge computing is …

Transfer learning for future wireless networks: A comprehensive survey

CT Nguyen, N Van Huynh, NH Chu, YM Saputra… - arXiv preprint arXiv …, 2021 - arxiv.org
With outstanding features, Machine Learning (ML) has been the backbone of numerous
applications in wireless networks. However, the conventional ML approaches have been …

[HTML][HTML] Cache in fog computing design, concepts, contributions, and security issues in machine learning prospective

MA Naeem, YB Zikria, R Ali, U Tariq, Y Meng… - Digital Communications …, 2023 - Elsevier
The massive growth of diversified smart devices and continuous data generation poses a
challenge to communication architectures. To deal with this problem, communication …