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 …

Deep reinforcement learning approaches for content caching in cache-enabled D2D networks

L Li, Y Xu, J Yin, W Liang, X Li… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Internet of Things (IoT) technology suffers from the challenge that rare wireless network
resources are difficult to meet the influx of a huge number of terminal devices. Cache …

Online proactive caching in mobile edge computing using bidirectional deep recurrent neural network

L Ale, N Zhang, H Wu, D Chen… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
With emergence of Internet of Things (IoT), wireless traffic has grown dramatically, posing
severe strain on core network and backhaul bandwidth. Proactive caching in mobile edge …

Learning distributed caching strategies in small cell networks

A Sengupta, SD Amuru, R Tandon… - 2014 11th …, 2014 - ieeexplore.ieee.org
Caching has emerged as a vital tool in modern communication systems for reducing peak
data rates by allowing popular files to be pre-fetched and stored locally at end users' …

Deep learning-based edge caching in fog radio access networks

Y Jiang, H Feng, FC Zheng, D Niyato… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this article, the edge caching policy in fog radio access networks (F-RANs) is optimized
via deep learning. Considering that it is hard for fog access points (F-APs) to collect sufficient …

Artificial intelligence for wireless caching: Schemes, performance, and challenges

M Sheraz, M Ahmed, X Hou, Y Li, D Jin… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Wireless data traffic is growing unprecedentedly and it may impede network performance by
consuming an ever-greater amount of bandwidth. With the advancement in technology there …

Federated deep reinforcement learning for recommendation-enabled edge caching in mobile edge-cloud computing networks

C Sun, X Li, J Wen, X Wang, Z Han… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
To support rapidly increasing services and applications from users, multi-tier computing is
emerged as a promising system-level computing architecture by distributing …

Multi-agent reinforcement learning based cooperative content caching for mobile edge networks

W Jiang, G Feng, S Qin, Y Liu - IEEE Access, 2019 - ieeexplore.ieee.org
To address the drastic growth of data traffic dominated by streaming of video-on-demand
files, mobile edge caching/computing (MEC) can be exploited to develop intelligent content …

Content popularity prediction towards location-aware mobile edge caching

P Yang, N Zhang, S Zhang, L Yu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Mobile edge caching aims to enable content delivery within the radio access network, which
effectively alleviates the backhaul burden and reduces response time. To fully exploit edge …

Rl-cache: Learning-based cache admission for content delivery

V Kirilin, A Sundarrajan, S Gorinsky… - Proceedings of the 2019 …, 2019 - dl.acm.org
Content delivery networks (CDNs) distribute much of the Internet content by caching and
serving the objects requested by users. A major goal of a CDN is to maximize the hit rates of …