Name
Abstract | ||
|---|---|---|
Cloud computing is one technology developed for large-scale resource sharing and service-oriented computing. Since, cloud computing is a service-oriented computing, performance analysis of cloud service becomes an important issue. Due to the complexity of the cloud computing system, it is difficult to analyze the service performance. Although there exist some researches on cloud service, very few of them addressed the issues of reliability and its impact on service performance in the virtual resources pool constructed by heterogeneous physical resources. In order to analyze performance considering reliability, this paper presents a reliability-performance correlation model. By using the Markov model, the universal generating function and the Markov reward model, the correlation model first analyzes performance with considering physical machine failures and VM failures simultaneously in a heterogeneous environment. In addition, compared with traditional models, our model is realistic model that can support dividing a job into many subtasks (e.g., MapReduce). And the performance index of efficient service rate can be obtained. Numerical examples are presented to verify the validity of our model. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/QRS-C.2016.52 | 2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) |
Keywords | Field | DocType |
cloud service,performance,reliability,Markov model,u-function,Markov reward model | Markov reward model,Division (mathematics),Computer science,Markov model,Utility computing,Shared resource,Cloud testing,Computing systems,Cloud computing,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-5090-3714-8 | 2 | 0.38 |
References | Authors | |
12 | 5 | |