Reinforcement learning-based optimal computing and caching in mobile edge network

Y Qian, R Wang, J Wu, B Tan… - IEEE Journal on Selected …, 2020 - ieeexplore.ieee.org
Joint pushing and caching are commonly considered an effective way to adapt to tidal
effects in networks. However, the problem of how to precisely predict users' future requests …

Dynamic content update for wireless edge caching via deep reinforcement learning

P Wu, J Li, L Shi, M Ding, K Cai… - IEEE Communications …, 2019 - ieeexplore.ieee.org
This letter studies a basic wireless caching network, where a source server is connected to a
cache-enabled base station (BS) that serves multiple requesting users. A critical problem is …

Joint user scheduling and content caching strategy for mobile edge networks using deep reinforcement learning

Y Wei, Z Zhang, FR Yu, Z Han - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Caching popular contents at the edge of mobile networks is an effective technology to
relieve burden on backhaul links and reduce average transmission delay. However, the …

Deep reinforcement learning-based edge caching in wireless networks

C Zhong, MC Gursoy… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the purpose to offload data traffic in wireless networks, content caching techniques
have recently been studied intensively. Using these techniques and caching a portion of the …

Joint optimization of preference-aware caching and content migration in cost-efficient mobile edge networks

P Lin, Z Ning, Z Zhang, Y Liu, FR Yu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Current mobile networks are facing dramatic growth in wireless traffics due to the prosperity
of streaming media services. Cooperative edge caching, enabling multiple edge nodes to …

Deep reinforcement learning for cooperative edge caching in future mobile networks

D Li, Y Han, C Wang, GT Shi, X Wang… - 2019 IEEE Wireless …, 2019 - ieeexplore.ieee.org
To satisfy rapidly increasing multimedia service requests from mobile users, content caching
at the network edges (eg, base stations) has been regarded as a promising technique in …

Proactive content caching based on actor–critic reinforcement learning for mobile edge networks

W Jiang, D Feng, Y Sun, G Feng… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Mobile edge caching/computing (MEC) has emerged as a promising approach for
addressing the drastic increasing mobile data traffic by bringing high caching and computing …

Deep reinforcement learning for adaptive caching in hierarchical content delivery networks

A Sadeghi, G Wang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Caching is envisioned to play a critical role in next-generation content delivery infrastructure,
cellular networks, and Internet architectures. By smartly storing the most popular contents at …

A survey on reinforcement learning-aided caching in heterogeneous mobile edge networks

N Nomikos, S Zoupanos, T Charalambous… - IEEE Access, 2022 - ieeexplore.ieee.org
Mobile networks experience a tremendous increase in data volume and user density due to
the massive number of coexisting users and devices. An efficient technique to alleviate this …

[PDF][PDF] A DQN-based cache strategy for mobile edge networks

S Sun, J Zhou, J Wen, Y Wei, X Wang - Computers, Materials & …, 2022 - academia.edu
The emerging mobile edge networks with content caching capability allows end users to
receive information from adjacent edge servers directly instead of a centralized data …