Software reliability and cost analysis considering service user for cloud with big data
Software reliability and cost analysis considering service user for cloud with big data
复制标题
大数据云考虑服务用户的软件可靠性和成本分析
DOI：
10.1142/s0218539317500097
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
and Shigeru Yamada
中科院分区：
文献类型：
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作者：
Yoshinobu Tamura;Tomoya Takeuchi;and Shigeru Yamada
目前，大数据云计算被称为下一代软件服务范式。然而，在大数据和云计算环境下，有效的软件可靠性分析方法却很少被提出。特别是，在使用大数据的云计算方面考虑最佳数据分区非常重要。考虑到云计算与大数据，这将是有用的软件管理人员估计的总软件成本，以使分配的最佳数据区域的云用户。针对云计算大数据环境下的数据最优划分问题，提出了一种基于神经网络的面向构件的可靠性评估方法。在此基础上，提出了基于云计算大数据的跳扩散过程模型的系统级可靠性评估方法。在此基础上，提出了基于跳扩散模型的最优维修问题。考虑到最大数量的用户作为云用户的合同成本，我们找到了最佳的维护时间，通过最小化总的软件成本。
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.