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Machine learning technologies for secure vehicular communication in internet of vehicles: recent advances and applications
Recently, interest in Internet of Vehicles'(IoV) technologies has significantly emerged due to
the substantial development in the smart automobile industries. Internet of Vehicles' …
the substantial development in the smart automobile industries. Internet of Vehicles' …
Management and orchestration of edge computing for IoT: A comprehensive survey
With the development of telecommunication technologies and the proliferation of network
applications in the past decades, the traditional cloud network architecture becomes unable …
applications in the past decades, the traditional cloud network architecture becomes unable …
Multiagent deep reinforcement learning for vehicular computation offloading in IoT
X Zhu, Y Luo, A Liu, MZA Bhuiyan… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The development of the Internet of Things (IoT) and intelligent vehicles brings a comfortable
environment for users. Various emerging vehicular applications using artificial intelligence …
environment for users. Various emerging vehicular applications using artificial intelligence …
Joint optimization strategy of computation offloading and resource allocation in multi-access edge computing environment
In order to help user terminal devices (UTDs) efficiently handle computation-intensive and
time-delay sensitive computing task, multi-access edge computing (MEC) has been …
time-delay sensitive computing task, multi-access edge computing (MEC) has been …
DeepEdge: A new QoE-based resource allocation framework using deep reinforcement learning for future heterogeneous edge-IoT applications
Edge computing is emerging to empower the future of Internet of Things (IoT) applications.
However, due to heterogeneity of applications, it is a significant challenge for the edge cloud …
However, due to heterogeneity of applications, it is a significant challenge for the edge cloud …
Optimized multi-service tasks offloading for federated learning in edge virtualization
Edge federated learning (EFL) utilizes edge computing (EC) to alleviate direct round
communications of multi-dimensional model updates between local participants and the …
communications of multi-dimensional model updates between local participants and the …
Machine learning technologies in internet of vehicles
Recently, there was much interest in Technology which has emerged greatly to the
development of smart cars. Internet of Vehicle (IoV) enables vehicles to communicate with …
development of smart cars. Internet of Vehicle (IoV) enables vehicles to communicate with …
Offloading decision and resource allocation in mobile edge computing for cost and latency efficiencies in real-time IoT
Internet of Things (IoT) devices can integrate with applications requiring intensive contextual
data processing, intelligent vehicle control, healthcare remote sensing, VR, data mining …
data processing, intelligent vehicle control, healthcare remote sensing, VR, data mining …
Mobility-aware deep reinforcement learning with seq2seq mobility prediction for offloading and allocation in edge computing
Mobile/multi-access edge computing (MEC) is developed to support the upcoming AI-aware
mobile services, which require low latency and intensive computation resources at the edge …
mobile services, which require low latency and intensive computation resources at the edge …
Edge-based video surveillance with graph-assisted reinforcement learning in smart construction
The smart construction site is develo** rapidly with the intelligentization of industrial
management. Intelligent devices are being widely deployed in construction industry to …
management. Intelligent devices are being widely deployed in construction industry to …