Assessment Model of Job Delay for Variant Data Scale Processing on Cloud Computing

Abstract

Cloud computing has shown the great computing power and superior capability for distributed computing applications in the past few years. A variety of cloud applications are spring up at amazing speed due to wide demands. With the divergent demands and applications, it is pretty hard to model the job execution delay for jobs with variant scale data processing on a cloud system. Accordingly, this paper is intended to address the issue concerning how to estimate job delay on a cloud system by applying the queuing model. The experimental results on a real cloud application are in favor of the usability and performance of proposed model.