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What-If Model Construction and Validation of Web Systems Based on Log Mining

机译:基于日志挖掘的Web系统假设模型构建与验证

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To maintain a complex modern web-based system, the what-if analysis is quite useful for predicting the impact of any workload growth or planned change on the performance of individual components, even the entire system. In this paper we propose an approach based on log mining to build what-if models of web-based systems and validate them by using OPNET simulation tool. Three contributions of this paper are: (1) the construction of what-if models based on log mining to automate the task of modeling and validation, (2) the technique to address complexity of user behaviors including users' browser caching, clustering of requests and users, etc., (3) and two real-life cases to evaluate the effectiveness and accuracy of this approach. The preliminary results show that the relative errors between logged data and simulation results are less than 18% in most cases including number of requests and network throughput.
机译:为了维护复杂的,基于Web的现代系统,假设分析对于预测任何工作负载增长或计划的更改对单个组件甚至整个系统的性能的影响非常有用。在本文中,我们提出了一种基于日志挖掘的方法来构建基于Web的系统的假设模型,并使用OPNET仿真工具对其进行验证。本文的三个贡献是:(1)基于日志挖掘的假设模型的构建,以自动化建模和验证任务;(2)解决用户行为复杂性的技术,包括用户的浏览器缓存,请求的聚类和用户等,(3)和两个实际案例来评估这种方法的有效性和准确性。初步结果表明,在大多数情况下,包括请求数和网络吞吐量,记录数据和模拟结果之间的相对误差小于18%。

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