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Multi-perspective Evaluation of Self-Healing Systems Using Simple Probabilistic Models

机译:使用简单概率模型的自我修复系统多视角评估

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In this paper we construct an evaluation framework for a self-healing system, VM-Rejuv - a virtual machine based rejuvenation scheme for web-application servers - using simple, yet powerful, probabilistic models that capture the behavior of its self-healing mechanisms from multiple perspectives (designer, operator, and end-user). We combine these analytical models with runtime fault-injection to study the operation of VM-Rejuv, and use the results from the fault-injection experiments and model-analysis to reason about the efficacy of VM-Rejuv, its limitations and strategies for mitigating these limitations in system-deployments. Whereas we use VM-Rejuv as the subject of our evaluation in this paper, our main contribution is the demonstration of a practical evaluation approach that can be generalized to other self-healing systems.
机译:在本文中,我们构建了一个自我修复系统的评估框架,VM-REJUV - 一种基于虚拟机的Web应用程序服务器的复兴方案 - 使用简单但功能强大的概率模型,从而捕获其自我修复机制的行为多个透视图(设计师,运营商和最终用户)。我们将这些分析模型与运行时的故障注射结合起来研究VM-Rejuv的操作,并使用故障注射实验的结果和模型分析,以推动VM-Rejuv,其限制和减轻这些策略的效果系统部署的限制。虽然我们使用VM-REJUV作为我们评估的主题,但我们的主要贡献是证明可以推广到其他自我修复系统的实际评估方法。

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