Optimization and Reliability Analysis Tool Based on Multi-Dimensional Wiener Processes for Big Data on Cloud Computing  
Author Yoshinobu Tamura

 
Co-Author(s) Shigeru Yamada

 
Abstract This paper focuses on a big data on cloud computing environment by using open source software such as OpenStack and Eucalyptus because of the unification management of data and low cost. We discuss a new approach to software dependability assessment based on stochastic differential equation modeling in order to consider the interesting aspect of the numbers of components, cloud applications, and users. Moreover, we consider the determination of an optimum software maintenance time minimizing the total expected software cost. In particular, we develop the three-dimensional AIR application for reliability and cost optimization analysis based on the proposed method. Then, we show numerical performance of the developed AIR application to evaluate the method of software reliability assessment for the big data on cloud computing.

 
Keywords Optimization, Reliability, Software Tool, Big Data, Cloud Computing
   
    Article #:  23-185
 
Proceedings of the 23rd ISSAT International Conference on Reliability and Quality in Design
August 3-5, 2017 - Chicago, Illinois, U.S.A.