… We have considered a typical IoV network architecture with one IoV Edge-Computing (IoVEC)
and one mobile user. The tasks of the device arrive as a flow in time. Our analytical model …

… In [13], the authors propose a comprehensive survey on resource allocation schemes for
IoV, including cellular networks and Dedicated Short Range Communications (DSRC). On the …

… efficiency through optimal RSU placement and enhance security with a malicious IoV detection
algorithm in an SD-IoV network. Therefore, the memetic-based RSU (M-RSU) placement …

… Machine Learning for enhancing Slice Orchestration and Management. Also, we will explore
how Machine learning … Also, the Machine Learning approach will automatically update its …

… resource among smart vehicles with highlevel intelligence in IoV networks. Reinforcement
learning (RL) is one of the most powerful machine learning tools for policy control and …

… machine learning method is presented to predict optimal energy consumption between
vehicles to transfer data with safe and secured infrastructure in the IoV … ad hoc network (VANET). …

… an important issue in future IoV trends. Artificial Intelligence (AI) technology with Machine
Learning (ML) mechanisms offers smart solutions that can improve IoV network efficiency. For …

… the Internet of Vehicles (IoV), an optimal … IoV. The blockchain system is used as the storage
structure for relay data, and the smart contract incentive algorithm based on machine learning …

… vehicular network resources. To achieve this, we propose a cluster-based CRassisted IoV
network called CRAV-Net. We devised a novel congestion-aware hybrid learning solution for …

… , misbehavior detection can be performed by creating a machine learning model from basic
… system for IoV using Federated Machine Learning. Vehicles in VANET for IoV are given the …