A Talpur, M Gurusamy - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
… the basics of vehicularnetworks and different types of communications. Apart from the traditional vehicularnetworks, we also consider modern vehicularnetwork architectures. We …
L Liang, H Ye, GY Li - IEEE Internet of Things Journal, 2018 - ieeexplore.ieee.org
… of high mobility vehicularnetworks and motivate the use of machinelearning to address the … of machinelearning, we discuss its applications to learn the dynamics of vehicularnetworks …
… to apply advanced machinelearning into vehicular communications and networking. It … ML-enabled evolution for vehicularnetworks in terms of communication, networking, and security …
… of modern vehicular Internet … networks has made it somewhat tricky to manage network slicing efficiently. This paper also presents a proof of concept for leveraging machinelearning-…
H Ye, L Liang, GY Li, JB Kim, L Lu, M Wu - arXiv preprint arXiv:1712.07143, 2017 - arxiv.org
… in applying machinelearning in vehicularnetworks and attempt … machinelearning, we present some application examples of machinelearning in solving problems arising in vehicular …
… vehicularnetworks using machinelearning. Therefore, a thorough understanding of how machinelearning … a dynamic resource allocation in vehicularnetworks is provided in this study. …
H El-Sayed, HA Ignatious, P Kulkarni… - Vehicular Communications, 2020 - Elsevier
… We have introduced machinelearning concepts to frame trust rules and Artificial Neural Network (ANN) to selftrain the vehicular nodes to ensure reliable message propagation. …
… 2.2 MachineLearning Based IDS for Network Intrusion Detection Machinelearning based … for VANET that combines both machinelearning and Dempster-Shafer theory is proposed. …
… enables machinelearning integration in the communication system including the vehicular … demand of future vehicularnetworks. A MEC-based framework is proposed for autonomous …