Priority-Based Cloud Computing Architecture for Multimedia-Enabled Heterogeneous Vehicular Users

In recent days, vehicles have been equipped with smart devices that offer various multimedia-related applications and services, such as smart driving assistance, traffic congestions, weather forecasting, road safety alarms, and many entertainment and comfort applications. Thus, these smart vehicles produce a large amount of multimedia-related data that require fast and real-time processing. However, due to constrained computing and storage capacities, such huge amounts of multimedia-related data cannot be processed in on-board standalone devices. Thus, multimedia cloud computing (MCC) has emerged as an economical and scalable computing technology that can process multimedia-related data efficiently while providing improved Quality of Service (QoS) to vehicular users from anywhere, at any time and on any device, at reduced costs. However, there are certain challenges, such as fast service response time and resource cost optimization, that can severely affect the performance of the MCC. Therefore, to tackle these issues, in this paper, we propose a dynamic priority-based architecture for the MCC. In the proposed scheme, we divide multimedia processing into four different subphases, while computing resources to each computing server are assigned dynamically, according to the workload, in order to process multimedia tasks according to the multimedia user Quality of Experience (QoE) requirements. The performance of the proposed scheme is evaluated in terms of service response time and resource cost optimization using the CloudSim simulator.