Offloading using traditional optimization and machine learning in federated cloud–edge–fog systems: A survey

B Kar, W Yahya, YD Lin, A Ali - IEEE Communications Surveys …, 2023 - ieeexplore.ieee.org
The huge amount of data generated by the Internet of Things (IoT) devices needs the
computational power and storage capacity provided by cloud, edge, and fog computing …

Classifications and applications of physical layer security techniques for confidentiality: A comprehensive survey

JM Hamamreh, HM Furqan… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Physical layer security (PLS) has emerged as a new concept and powerful alternative that
can complement and may even replace encryption-based approaches, which entail many …

Resource management approaches in fog computing: a comprehensive review

M Ghobaei-Arani, A Souri, AA Rahmanian - Journal of Grid Computing, 2020 - Springer
In recent years, the Internet of Things (IoT) has been one of the most popular technologies
that facilitate new interactions among things and humans to enhance the quality of life. With …

A cooperative partial computation offloading scheme for mobile edge computing enabled Internet of Things

Z Ning, P Dong, X Kong, F **a - IEEE Internet of Things Journal, 2018 - ieeexplore.ieee.org
With the evolutionary development of latency sensitive applications, delay restriction is
becoming an obstacle to run sophisticated applications on mobile devices. Partial …

Reliable computation offloading for edge-computing-enabled software-defined IoV

X Hou, Z Ren, J Wang, W Cheng, Y Ren… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Internet of Vehicles (IoV) has drawn great interest recent years. Various IoV applications
have emerged for improving the safety, efficiency, and comfort on the road. Cloud computing …

Deep learning for smart industry: Efficient manufacture inspection system with fog computing

L Li, K Ota, M Dong - IEEE Transactions on Industrial …, 2018 - ieeexplore.ieee.org
With the rapid development of Internet of things devices and network infrastructure, there
have been a lot of sensors adopted in the industrial productions, resulting in a large size of …

Imitation learning enabled task scheduling for online vehicular edge computing

X Wang, Z Ning, S Guo, L Wang - IEEE Transactions on Mobile …, 2020 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a promising paradigm based on the Internet of vehicles
to provide computing resources for end users and relieve heavy traffic burden for cellular …

SDN/NFV-empowered future IoV with enhanced communication, computing, and caching

W Zhuang, Q Ye, F Lyu, N Cheng… - Proceedings of the …, 2019 - ieeexplore.ieee.org
Internet-of-Vehicles (IoV) connects vehicles, sensors, pedestrians, mobile devices, and the
Internet with advanced communication and networking technologies, which can enhance …

Deep reinforcement learning for vehicular edge computing: An intelligent offloading system

Z Ning, P Dong, X Wang, JJPC Rodrigues… - ACM Transactions on …, 2019 - dl.acm.org
The development of smart vehicles brings drivers and passengers a comfortable and safe
environment. Various emerging applications are promising to enrich users' traveling …

Deep reinforcement learning for collaborative edge computing in vehicular networks

M Li, J Gao, L Zhao, X Shen - IEEE Transactions on Cognitive …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising technology to support mission-critical
vehicular applications, such as intelligent path planning and safety applications. In this …