Research Article
An Novel Approach to Evaluate the Reliability of Cloud Rendering System Using Probabilistic Model Checker PRISM : A Quantitative Computing Perspective
@INPROCEEDINGS{10.4108/eai.7-11-2017.2273297, author={Haoyu Liu and Huahu Xu and Honghao Gao and Minjie Bian and Huaikou Miao}, title={An Novel Approach to Evaluate the Reliability of Cloud Rendering System Using Probabilistic Model Checker PRISM : A Quantitative Computing Perspective}, proceedings={14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services}, publisher={ACM}, proceedings_a={MOBIQUITOUS}, year={2018}, month={4}, keywords={cloud rendering; dtmc model checking; prism; reliability}, doi={10.4108/eai.7-11-2017.2273297} }- Haoyu Liu
Huahu Xu
Honghao Gao
Minjie Bian
Huaikou Miao
Year: 2018
An Novel Approach to Evaluate the Reliability of Cloud Rendering System Using Probabilistic Model Checker PRISM : A Quantitative Computing Perspective
MOBIQUITOUS
ACM
DOI: 10.4108/eai.7-11-2017.2273297
Abstract
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.