Intelligent transportation systems rely on smart vehicles equipped with various sensing devices to offer a range of multimedia applications and services for driving assistance, traffic congestion information, weather forecasting, road safety alarms, and entertainment and comfort-related features. However, the large amount of multimedia-related data produced by these vehicles cannot be handled by standalone onboard computing devices due to their limited computational power and storage capacity. As a result, changes in the networking and computing models are required to support these multimedia applications and services. Cloud computing has emerged as a promising computing paradigm for integrating vehicles with the cloud. However, challenges related to multimedia content processing, such as resource cost, fast service response time, and quality of experience, can significantly impact vehicular communication performance. To address these challenges, we propose an efficient resource allocation and computation framework for vehicular multimedia cloud computing. The proposed scheme's performance is evaluated using the Cloudsim simulator in terms of quality of experience, service response time, and resource cost.

Intelligent transportation system, smart vehicles, efficient resource allocation, and cloud computing.