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Combined Approach to Reliability of Great Software Complexes for Distributed Computing with Big Data in Contemporary Physical Experiments

机译:当代物理实验中用于大数据的分布式计算的大型软件组合可靠性的组合方法

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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.
机译:在未来十年中,科学数据管理的新挑战时代被称为“大数据”,它需要用于分布式计算和相应的网格云互联网服务的大型综合体。基于概率论或将软件视为开放的非平衡动态系统的已知软件可靠性通用方法无法符合高级网格云软件管理系统的要求。因此,为了提供此类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。 JINR Dubna信息技术实验室开发了一种新的网格和云服务仿真系统,该系统致力于通过使用某些实际系统的工作质量指标来设计和预测其发展,从而提高网格-云系统开发的效率和可靠性。为此,仿真程序通过一个特殊的数据库与gridcloud服务的真实监控系统结合在一起。给出了一些程序应用程序示例,它们可以模拟足够通用的云结构,并将其用于更常见的目的。

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