Machine Learning Technologies for Secure Vehicular Communication in Internet of Vehicles: Recent Advances and Applications

Table 2

Artificial intelligence methods in IoV QoS/QoE optimization.

Year	Source	Approaches	Features	Advantages	Challenges	Citations
2020	Sensors	Reinforcement learning; centralized Q-learning	Energy optimization with 5G vehicular social networks	Maximize the energy efficiency and optimization	Ensure communication quality and reduce delays	Park and Lim [33]
2019	IJEAT	SDN-based ML (BAT algorithm)	Prioritize the data packets in IoT cloud storage	Enhance traffic QoS	Traffic delay reduction in IoT multimedia applications	Hasan et al. [28]
2019	Elsevier	Fuzzy-enabled algorithms for buffer and power-aware QoE optimization.	AI-based multimedia communication mechanism and IoV-based QoE optimization framework	Improve multimedia streaming for end users	QOE optimization for multimedia communication in IoV	Sodhro [14]
2018	IEEE	QoE-based ML for video admission control and resource management	Extracting the quality-rate characteristics of unknown video sequences	Improve the service and quality level delivered to end user	Guarantee a minimum service quality level	Islam et al. [30]
2017	EAI	Many-to-one matching game; Stable Matching Algorithm (SMA); Pareto Optimal Matching Algorithm (POMA)	Traveling plan-aware scheduling scheme for EV charging in driving pattern	Improve the QoE in vehicle power grid networks	QoE enhancement in EV industry	Bozkaya and Canberk [34]
2016	Science PG	Fuzzy QoS	Enhance energy efficiency in IoV	Optimize energy QoS	Trade-off between QoS and energy efficiency	Hu [29]