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A Software Reliability Model for Cloud-Based Software Rejuvenation Using Dynamic Fault Trees

机译:基于动态故障树的基于云的软件复兴的软件可靠性模型

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Correctly measuring the reliability and availability of a cloud-based system is critical for evaluating its system performance. Due to the promised high reliability of physical facilities provided for cloud services, software faults have become one of the major factors for the failures of cloud-based systems. In this paper, we focus on the software aging phenomenon where system performance may be progressively degraded due to exhaustion of system resources, fragmentation and accumulation of errors. We use a proactive technique, called software rejuvenation, to counteract the software aging problem. The dynamic fault tree (DFT) formalism is adopted to model the system reliability before and during a software rejuvenation process in an aging cloud-based system. A novel analytical approach is presented to derive the reliability function of a cloud-based Hot SPare (HSP) gate, which is further verified using Continuous Time Markov Chains (CTMC) for its correctness. We use a case study of a cloud-based system to illustrate the validity of our approach. Based on the reliability analytical results, we show how cost-effective software rejuvenation schedules can be created to keep the system reliability consistently staying above a predefined critical level.
机译:正确测量基于云的系统的可靠性和可用性对于评估其系统性能至关重要。由于承诺为云服务提供的物理设施的高度可靠性,软件故障已成为基于云的系统故障的主要因素之一。在本文中,我们关注软件老化现象,其中由于系统资源耗尽,碎片和错误累积,系统性能可能会逐渐降低。我们使用一种称为软件更新的主动技术来解决软件老化问题。在基于云的老化系统中,在软件复兴过程之前和期间,采用动态故障树(DFT)形式来对系统可靠性进行建模。提出了一种新颖的分析方法来推导基于云的热备用(HSP)门的可靠性功能,并使用连续时间马尔可夫链(CTMC)对其进行了正确性进一步验证。我们使用基于云的系统的案例研究来说明我们方法的有效性。基于可靠性分析结果,我们展示了如何创建具有成本效益的软件更新计划,以使系统可靠性始终保持在预定义的关键水平之上。

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