Software Reliability and Cost Analysis Considering Service User for Cloud with Big Data
Y. Tamuraa✉, Tomoya Takeuchib, S. Yamadab
- aDepartment of Engineering, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Tokiwadai 2-16-1, Ube-shi, Yamaguchi, 755-8611, Japan
- bDepartment of Social Management Engineering, Graduate School of Engineering, Tottori University, Minami 4-101, Koyama, Tottori-shi, 680-8552, Japan
- ✉Corresponding author
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Abstract
At present, the cloud computing with big data is known as a next-generation software service paradigm. However, the effective methods of software reliability analysis considering the big data and cloud computing have been only few presented. In particular, it is important to consider the optimal data partitioning in terms of cloud computing with big data. Considering the cloud computing with big data, it will be useful for the software managers to estimate the total software cost in order to make allocations the optimal data area to the cloud user. We propose the method of component-oriented reliability assessment based on neural network in order to the optimal data partitioning for cloud computing with big data in this paper. Moreover, we propose the method of system-wide reliability assessment based on the jump diffusion process model considering the big data on cloud computing. Furthermore, we propose the optimal maintenance problem based on the jump diffusion model. Considering the contract cost for the maximum number of subscriber as the cloud user, we find the optimum maintenance time by minimizing the total software cost.
TL;DRThis paper proposes the method of component-oriented reliability assessment based on neural network in order to the optimal data partitioning for cloud computing with big data and proposes the optimal maintenance problem based on the jump diffusion model. (Semantic Scholar)