当代物理实验中大数据分布式计算软件复合体可靠性研究

G. Ososkov
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引用次数: 0

摘要

未来十年,科学数据管理的新挑战时代被称为“大数据”,需要庞大的分布式计算综合体和相应的网格云互联网服务。基于概率论或将软件视为开放的非平衡动态系统的已知通用软件可靠性方法不符合先进的网格云软件管理系统。因此,为了提供这种复杂系统的最优性和可靠性,我们选择了基于系统功能动力学知识的模拟仿真方法。在天津大学杜布纳信息技术实验室开发了一套新的网格与云服务仿真系统,该系统旨在利用某些实际系统的工作质量指标来设计和预测其演变,从而提高网格云系统开发的效率和可靠性。为此,通过专门的数据库将仿真程序与网格云服务的实际监控系统相结合。给出了一些应用程序来模拟足够一般的云结构的例子,这些云结构可以用于更常见的目的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined Approach to Reliability of Great Software Complexes for Distributed Computing with Big Data in Contemporary Physical Experiments
The new challenging era of scientific data management in the coming decade named "Big Data" requires giant complexes for distributed computing and corresponding grid-cloud internet services. Known common approaches to software reliability based on the probability theory or on considering software as an open non-equilibrium dynamic system cannot conform to advanced grid-cloud software management systems. Therefore to provide the optimality and reliability of such sophisticated systems we choose the imitative simulation method oriented on a knowledge of dynamics of the system functioning. A new grid and cloud service simulation system was developed in the JINR Dubna laboratory of information technologies which focused on improving the efficiency and reliability of the grid-cloud systems development by using work quality indicators of some real system to design and predict its evolution. For these purposes the simulation program is combined with real monitoring system of the gridcloud service through a special database. Some examples of the program applications to simulate a sufficiently general cloud structure, which can be used for more common purposes, are given.
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