Survival of the Internet applications: a cluster recovery model

Khin Mi Mi Aung, Kiejin Park, Jong Sou Park
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引用次数: 4

Abstract

Internet applications become increasingly widely used for millions of people in the world and on the other hand the accidents or disruptions of service are also dramatically increasing. Accidents or disruptions occur either because of disasters or because of malicious attacks. The disasters could not be completely prevented. Prevention is a necessary but not a sufficient component of disaster. In this case, we have to prepare thoroughly for reducing the recovery time and get the users back to work faster. In this paper, we present a cluster recovery model to increase the survivability level of Internet applications. We construct a state transition model to describe the behaviors of cluster systems. By mapping through recovery actions to this transition model with stochastic process, we capture system behaviors as well as we get mathematical steady-state solutions of that chain. We first carry out for steady-state behaviors leading to measures like steady-state availability. By transforming this model with the system states we compute a system measure, the mean time to repair (MTTR) and also compute probabilities of cluster systems failures due in face of disruptions. Our model with the recovery actions have several benefits, which include reducing the time to get the users back to work and making recovery performance insensitive to the selection of a failure treatment parameter
因特网应用程序的生存:一个集群恢复模型
互联网应用程序越来越广泛地为世界上数百万人使用,另一方面,服务的事故或中断也急剧增加。事故或中断的发生要么是因为灾难,要么是因为恶意攻击。灾难是无法完全避免的。预防是灾难的必要组成部分,但不是充分组成部分。在这种情况下,我们必须做好充分的准备,减少恢复时间,让用户更快地恢复工作。在本文中,我们提出了一个集群恢复模型来提高互联网应用程序的生存水平。我们建立了一个状态转移模型来描述集群系统的行为。通过将恢复动作映射到这个具有随机过程的过渡模型,我们捕获了系统行为,并得到了该链的数学稳态解。我们首先执行稳态行为,从而得到稳态可用性等度量。通过将该模型与系统状态进行转换,我们计算了系统度量、平均修复时间(MTTR)以及面对中断时集群系统故障的概率。我们的带有恢复动作的模型有几个好处,包括减少让用户恢复工作的时间,使恢复性能对故障处理参数的选择不敏感
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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