Deep reinforcement learning for mobile edge caching: Review, new features, and open issues

H Zhu, Y Cao, W Wang, T Jiang, S Jin - IEEE Network, 2018 - ieeexplore.ieee.org
Mobile edge caching is a promising technique to reduce network traffic and improve the
quality of experience of mobile users. However, mobile edge caching is a challenging …

Cooperative content caching in 5G networks with mobile edge computing

K Zhang, S Leng, Y He, S Maharjan… - IEEE Wireless …, 2018 - ieeexplore.ieee.org
Along with modern wireless networks being content-centric, the demand for rich multimedia
services has been growing at a tremendous pace, which brings significant challenges to …

[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 …

Joint optimization of cooperative edge caching and radio resource allocation in 5G-enabled massive IoT networks

F Zhang, G Han, L Liu… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The fifth-generation of wireless communication (5G) is a promising paradigm toward
massive interconnectivity within Internet-of-Things (IoT) networks. However, because the …

On a novel adaptive UAV-mounted cloudlet-aided recommendation system for LBSNs

F Tang, ZM Fadlullah, B Mao, N Kato… - … on Emerging Topics …, 2018 - ieeexplore.ieee.org
Location Based Social Networks (LBSNs) have recently emerged as a hot research area.
However, the high mobility of LBSN users and the need to quickly provide access points in …

Secure content delivery with edge nodes to save caching resources for mobile users in green cities

Q Xu, Z Su, Q Zheng, M Luo… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
To save energy during content delivery in green cities, caching contents on edge nodes that
are placed near mobile social users has been advocated recently. However, how to allocate …

Proactive caching for vehicular multi-view 3D video streaming via deep reinforcement learning

Z Zhang, Y Yang, M Hua, C Li… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This paper investigates the problem of proactive caching for multi-view 3D videos in the fifth
generation (5G) networks. We establish a mathematical model for this problem, and point …

Sacc: A size adaptive content caching algorithm in fog/edge computing using deep reinforcement learning

X Zhou, Z Liu, M Guo, J Zhao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Edge/Fog caching is promising to mitigate the data traffic problem in both traditional
wireline/wireless networks and the 5G network. Recently, deep reinforcement learning …

A trustworthy content caching and bandwidth allocation scheme with edge computing for smart campus

Q Xu, Z Su, Y Wang, M Dai - IEEE Access, 2018 - ieeexplore.ieee.org
Edge computing enabled mobile social networks can improve mobile users' quality of
experience (QoE) when they exchange and share contents with each other. However, as …

Social-aware spectrum sharing and caching helper selection strategy optimized multicast video streaming in dense D2D 5G networks

NS Vo, TM Phan, MP Bui, XK Dang… - IEEE Systems …, 2020 - ieeexplore.ieee.org
The expected explosion of video traffic in 5G ultradense networks will pose many challenges
to the Internet service providers, eg, degraded capacity and unfair quality of service (QoS) …