Convergence of edge computing and deep learning: A comprehensive survey
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 …
massive amounts of data, and ever-increasing computing power is driving the core of …
A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …
generation (6G) mobile communication networks, ultrareliable and low-latency …
A survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art
Driven by the emergence of new compute-intensive applications and the vision of the
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …
Applications of deep reinforcement learning in communications and networking: A survey
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
Comprehensive survey on machine learning in vehicular network: technology, applications and challenges
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …
intelligence tool is widely researched to intelligentize communication and networking …
A survey on the computation offloading approaches in mobile edge computing: A machine learning-based perspective
A Shakarami, M Ghobaei-Arani, A Shahidinejad - Computer Networks, 2020 - Elsevier
With the rapid developments in emerging mobile technologies, utilizing resource-hungry
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …
A survey on computation offloading modeling for edge computing
H Lin, S Zeadally, Z Chen, H Labiod, L Wang - Journal of Network and …, 2020 - Elsevier
As a promising technology, edge computing extends computation, communication, and
storage facilities toward the edge of a network. This new computing paradigm opens up new …
storage facilities toward the edge of a network. This new computing paradigm opens up new …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
Joint computation offloading and task caching for multi-user and multi-task MEC systems: reinforcement learning-based algorithms
IA Elgendy, WZ Zhang, H He, BB Gupta… - Wireless …, 2021 - Springer
Computation offloading at mobile edge computing (MEC) servers can mitigate the resource
limitation and reduce the communication latency for mobile devices. Thereby, in this study …
limitation and reduce the communication latency for mobile devices. Thereby, in this study …
Resource allocation based on deep reinforcement learning in IoT edge computing
By leveraging mobile edge computing (MEC), a huge amount of data generated by Internet
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …