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

机译:具有当代物理实验中的大数据分布式计算的伟大软件复合体可靠性的组合方法

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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:未来十年的科学数据管理的新挑战时代命名为“大数据”,需要巨大的复合体进行分布式计算和相应的网格云互联网服务。基于概率理论或考虑软件作为开放式非平衡动态系统的概率可靠性的已知常见方法不能符合高级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,我们选择了对系统功能动态知识的模拟模拟方法。新的电网和云维修仿真系统是在信息技术的Jinr Dubna实验室开发的,这些技术通过使用一些真实系统的工作质量指标来改进网格云系统开发的效率和可靠性来设计和预测其演变。对于这些目的,仿真程序通过特殊数据库与GridCloud服务的实际监控系统组合。给出了模拟足够一般云结构的程序应用程序的一些示例,其可以用于更常用的目的。

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