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Run-Time Root Cause Analysis in Adaptive Distributed Systems

机译:自适应分布式系统中的运行时根本原因分析

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In a distributed environment, several components collaborate with each other to cater a complex functionality. Adaptation in distributed systems is one of the emerging trends that re-configures itself through components addition/removal/update, to cope up with faults. Components are generally inter-dependent, thus a fault propagates from one component to another. Existing root cause analysis techniques generally create a static faults' dependencies graph to identify the root fault. However, these dependencies keep on changing with adaptations that makes design-time fault dependencies invalid at run-time. This paper describes the problem of deriving causal relationships of faults in adaptive distributed systems. Then, presents a statechart-based solution that statically identifies the sequence of methods execution to derive the causal relationships of faults at run-time. The approach is evaluated, and found that it is highly scalable and time efficient that can be used to reduce the Mean Time To Recover (MTTR) of a distributed system.
机译:在分布式环境中,多个组件相互协作以实现复杂的功能。分布式系统中的适应性是新兴趋势之一,它通过添加/删除/更新组件来重新配置自身以应对故障。组件通常是相互依赖的,因此故障会从一个组件传播到另一个组件。现有的根本原因分析技术通常会创建静态故障的依存关系图以识别根本故障。但是,这些依存关系会随着适应的变化而不断变化,从而使设计时故障依存关系在运行时无效。本文描述了在自适应分布式系统中推导故障因果关系的问题。然后,提出了一种基于状态图的解决方案,该解决方案静态地标识了方法执行的顺序,以在运行时导出故障的因果关系。对这种方法进行了评估,发现它具有高度的可伸缩性和时间效率,可用于减少分布式系统的平均恢复时间(MTTR)。

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