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Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

机译:基于跳跃扩散模型和两个维纳过程的大数据云计算可靠性分析

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At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud computing changes depending on many external factors. We propose a jump diffusion model with two-dimensional Wiener processes in order to consider the interesting aspects of the network traffic and big data on cloud computing. In particular, we assess the stability of cloud software by using the sample paths obtained from the jump diffusion model with two-dimensional Wiener processes. Moreover, we discuss the optimal maintenance problem based on the proposed jump diffusion model. Furthermore, we analyze actual data to show numerical examples of dependability optimization based on the software maintenance cost considering big data on cloud computing.
机译:目前,由于数据的统一管理,成本降低,快速交付和节省工作量,许多云服务都通过使用开源软件(例如OpenStack和Eucalyptus)进行管理。云计算的操作阶段具有独特的功能,例如供应过程,基于网络的操作和数据的多样性,因为云计算的操作阶段取决于许多外部因素。为了考虑网络流量和云计算中大数据的有趣方面,我们提出了具有二维维纳过程的跳跃扩散模型。特别是,我们通过使用具有二维维纳过程的跳跃扩散模型获得的样本路径来评估云软件的稳定性。此外,我们基于提出的跳跃扩散模型讨论了最优维护问题。此外,我们分析实际数据以显示基于云计算中大数据的软件维护成本的可靠性优化的数值示例。

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