Efficient Resource Allocation for Multimedia Streaming in IoV Networks

“

As an individual, I find the publication "Efficient Resource Allocation for Multimedia Streaming in Software-Defined Internet of Vehicles" to be a significant and timely contribution to the field of Internet of Vehicles (IoV) networks. The study addresses the pressing challenges faced by IoV networks, such as the increasing growth of IoMV network and high-volume multimedia traffic, severe load variations during peak and non-peak hours, decline in Quality of Service (QoS) and Quality of Experience (QoE) during peak periods, and energy wastage during non-peak hours. The proposed ELQ2 architecture, designed for the integrated management of servers and switches within the IoMV network, offers a promising solution to optimize energy usage while providing users with high-quality multimedia streaming. The study's focus on the efficient management of resources, including energy, load, QoS, and QoE, is particularly relevant in the context of the rapid expansion of multimedia applications and the utilization of Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) technologies in IoV. The modular architecture of ELQ2, combined with the use of SDN and NFV, allows for dynamic adjustment of resource allocation based on demand, effectively reducing energy usage and enhancing various QoS and QoE parameters. Overall, the publication provides valuable insights into the complex challenges faced by IoV networks and offers a comprehensive framework for addressing these challenges. It has the potential to significantly impact the field by improving the efficiency and sustainability of multimedia streaming in the context of the Internet of Vehicles.

”