AI-empowered fog/edge resource management for IoT applications: A comprehensive review, research challenges and future perspectives
The proliferation of ubiquitous Internet of Things (IoT) sensors and smart devices in several
domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to …
domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to …
Reinforcement learning methods for computation offloading: a systematic review
Z Zabihi, AM Eftekhari Moghadam… - ACM Computing …, 2023 - dl.acm.org
Today, cloud computation offloading may not be an appropriate solution for delay-sensitive
applications due to the long distance between end-devices and remote datacenters. In …
applications due to the long distance between end-devices and remote datacenters. In …
Adaptive digital twin and multiagent deep reinforcement learning for vehicular edge computing and networks
Technological advancements of urban informatics and vehicular intelligence have enabled
connected smart vehicles as pervasive edge computing platforms for a plethora of powerful …
connected smart vehicles as pervasive edge computing platforms for a plethora of powerful …
6G wireless systems: A vision, architectural elements, and future directions
Internet of everything (IoE)-based smart services are expected to gain immense popularity in
the future, which raises the need for next-generation wireless networks. Although fifth …
the future, which raises the need for next-generation wireless networks. Although fifth …
Matching-theory-based low-latency scheme for multitask federated learning in MEC networks
Nowadays, there is an ever-increasing interests in federated learning, which allows end
devices to collaboratively train a global machine learning model in a decentralized …
devices to collaboratively train a global machine learning model in a decentralized …
A vision towards integrated 6G communication networks: Promising technologies, architecture, and use-cases
The evolution of the previous mobile communication generations has led to innovative goals
of the Internet of Everything (IoE) in the 5G. However, addressing all IoE-associated …
of the Internet of Everything (IoE) in the 5G. However, addressing all IoE-associated …
Meta-hierarchical reinforcement learning (MHRL)-based dynamic resource allocation for dynamic vehicular networks
With the rapid development of vehicular networks, there is an increasing demand for
extensive networking, computting, and caching resources. How to allocate multiple …
extensive networking, computting, and caching resources. How to allocate multiple …
Toward response time minimization considering energy consumption in caching-assisted vehicular edge computing
The advent of vehicular edge computing (VEC) has generated enormous attention in recent
years. It pushes the computational resources in close proximity to the data sources and thus …
years. It pushes the computational resources in close proximity to the data sources and thus …
Artificial Intelligence and Machine Learning as key enablers for V2X communications: A comprehensive survey
M Christopoulou, S Barmpounakis, H Koumaras… - Vehicular …, 2023 - Elsevier
The automotive industry is undergoing a profound digital transformation to create
autonomous vehicles. Vehicle-to-Everything (V2X) communications enable the provisioning …
autonomous vehicles. Vehicle-to-Everything (V2X) communications enable the provisioning …
[图书][B] Mobile edge computing
Y Zhang - 2022 - library.oapen.org
This is an open access book. It offers comprehensive, self-contained knowledge on Mobile
Edge Computing (MEC), which is a very promising technology for achieving intelligence in …
Edge Computing (MEC), which is a very promising technology for achieving intelligence in …