Edge computing with artificial intelligence: A machine learning perspective
Recent years have witnessed the widespread popularity of Internet of things (IoT). By
providing sufficient data for model training and inference, IoT has promoted the development …
providing sufficient data for model training and inference, IoT has promoted the development …
Wireless powered mobile edge computing networks: A survey
Wireless Powered Mobile Edge Computing (WPMEC) is an integration of Mobile Edge
Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve …
Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve …
Multi-agent reinforcement learning based resource management in MEC-and UAV-assisted vehicular networks
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
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 …
Edge intelligence: The confluence of edge computing and artificial intelligence
Along with the rapid developments in communication technologies and the surge in the use
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …
AI-based fog and edge computing: A systematic review, taxonomy and future directions
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
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 …
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) …
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 …
Machine learning for 6G wireless networks: Carrying forward enhanced bandwidth, massive access, and ultrareliable/low-latency service
To satisfy the expected plethora of demanding services, the future generation of wireless
networks (6G) has been mandated as a revolutionary paradigm to carry forward the …
networks (6G) has been mandated as a revolutionary paradigm to carry forward the …