D. Tang, Dileep Kumar, Sreeram Duvur, Øystein Torbjørnsen
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引用次数: 26
摘要
应用服务器是一个标准的中间件平台,用于部署基于web的业务应用程序,这些应用程序通常需要底层平台来提供高系统可用性和最小化事务损失。本文针对一个容错应用服务器系统——Sun Java system application server, Enterprise Edition 7,提出了一种基于度量的可用性建模和分析方法。本研究将层次马尔可夫奖励建模技术应用于目标软件系统。模型参数是根据实验室或现场测量保守估计的。该模型采用不确定性分析方法,从有限时间内无法精确测量或在客户现场可能变化很大的参数可能范围内随机抽样,获得平均系统可用性和置信区间。如本文所示,实验室测量、分析建模和不确定性分析的结合使用是一种有用的评估方法,它可以在规定的置信度水平上为新软件产品提供保守的可用性评估。
Availability measurement and modeling for an application server
Application server is a standard middleware platform for deploying Web-based business applications which typically require the underlying platform to deliver high system availability and to minimize loss of transactions. This paper presents a measurement-based availability modeling and analysis for a fault tolerant application server system - Sun Java System Application Server, Enterprise Edition 7. The study applies hierarchical Markov reward modeling techniques on the target software system. The model parameters are conservatively estimated from lab or field measurements. The uncertainty analysis method is used on the model to obtain average system availability and confidence intervals by randomly sampling from possible ranges of parameters that cannot be accurately measured in limited time frames or may vary widely in customer sites. As demonstrated in this paper, the combined use of lab measurement, analytical modeling, and uncertainty analysis is a useful evaluation approach which can provide a conservative availability assessment at stated confidence levels for a new software product.