Cloud computing has become one of the most dynamic and adoptable computing paradigms. Multimedia Cloud Computing (MCC) is one of today's hot research topic. MCC is proven to be a most dynamic and efficient platform for managing a large amount of multimedia contents with maximum deployment of computing and processing resources at the service provider instead of users. Resilience and dependability are two key constituents to assure the reliability and availability of any service in the presence of errors and system failures. The heterogeneous environ-B Muddesar Iqbal ment of MCC has given rise to various challenges related to resource allocation and task management. Antifragility is a key to such environments, to let the disorder drive the strength of these systems. This paper is mainly divided into three parts. The first part discusses in detail the available state-of-the-art related to resource management under MCC. Similarly, the second part presents the comprehensive literature review on the task management in MCC. The third part presents the critical analysis and open research issues in MCC which help the researcher to define their research objectives in the field of MCC.
In intelligent transportation system, smart vehicles are equipped with a variety of sensing devices those offer various multimedia applications and services related to smart driving assistance, weather forecasting, traffic congestion information, road safety alarms, and many entertainment and comfort-related applications. These smart vehicles produce a massive amount of multimedia related data that required fast and real-time processing which cannot be fully handled by the standalone onboard computing devices due to their limited computational power and storage capacities. Therefore, handling such multimedia applications and services demanded changes in the underlaying networking and computing models. Recently, the integration of vehicles with cloud computing is emerged as a challenging computing paradigm. However, there are certain challenges related to multimedia contents processing, (i.e., resource cost, fast service response time, and quality of experience) that severely affect the performance of vehicular communication. Thus, in this paper, we propose an efficient resource allocation and computation framework for vehicular multimedia cloud computing to overcome the aforementioned challenges. The performance of the proposed scheme is evaluated in terms of quality of experience, service response time, and resource cost by using the Cloudsim simulator. INDEX TERMS Intelligent transportation system, multimedia cloud computing, vehicular networks, quality of experience, multimedia contents processing, response time, smart vehicle.
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