Convergence of edge computing and deep learning: A comprehensive survey

X Wang, Y Han, VCM Leung, D Niyato… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

On mobile edge caching

J Yao, T Han, N Ansari - IEEE Communications Surveys & …, 2019 - ieeexplore.ieee.org
With the widespread adoption of various mobile applications, the amount of traffic in wireless
networks is growing at an exponential rate, which exerts a great burden on mobile core …

Novel edge caching approach based on multi-agent deep reinforcement learning for internet of vehicles

D Zhang, W Wang, J Zhang, T Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Along with the development of Internet of Vehicles (IoV) and wireless technology, the usage
of applications that require low latency, such as autonomous driving and intelligent …

A deep reinforcement learning-based framework for content caching

C Zhong, MC Gursoy… - 2018 52nd Annual …, 2018 - ieeexplore.ieee.org
Content caching at the edge nodes is a promising technique to reduce the data traffic in next-
generation wireless networks. Inspired by the success of Deep Reinforcement Learning …

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 …

Learn to cache: Machine learning for network edge caching in the big data era

Z Chang, L Lei, Z Zhou, S Mao… - IEEE Wireless …, 2018 - ieeexplore.ieee.org
The unprecedented growth of wireless data traffic not only challenges the design and
evolution of the wireless network architecture, but also brings about profound opportunities …

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 …

Caching transient data for Internet of Things: A deep reinforcement learning approach

H Zhu, Y Cao, X Wei, W Wang… - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
Connected devices in Internet-of-Things (IoT) continuously generate enormous amount of
data, which is transient and would be requested by IoT application users, such as …

A mobility-aware vehicular caching scheme in content centric networks: Model and optimization

Y Zhang, C Li, TH Luan, Y Fu, W Shi… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Edge caching is being explored as a promising technology to alleviate the network burden
of cellular networks by separating the computing functionalities away from cellular base …

Multi-agent deep reinforcement learning-based cooperative edge caching for ultra-dense next-generation networks

S Chen, Z Yao, X Jiang, J Yang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The soaring mobile data traffic demands have spawned the innovative concept of mobile
edge caching in ultra-dense next-generation networks, which mitigates their heavy traffic …