An Novel Approach to Evaluate the Reliability of Cloud Rendering System Using Probabilistic Model Checker PRISM : A Quantitative Computing Perspective

This paper proposes an approach to evaluate the reliability of cloud rendering system. After the requirement analysis, the rendering system was divided into three modules: preparing files, requesting resources, and rendering task execution. Each module may have an exception that will reduce reliability, and has the ability to recover it. To expose these details, the discrete-time Markov chain (DTMC) is improved to formalize the cloud rendering system. The model contains an abnormal state set representing exceptions and errors such as file corruption and failure to rendering subtasks. Then, a series of formal properties are defined to describe reliability in detail. The proposed method gives full consideration to the processes of rendering tasks. Finally, the properties are verified by performing PRISM in a quantitative way. The experiment shows that our method is effective to evaluate the reliability of the cloud rendering system.