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Application of Data Mining Algorithms to TCP throughput Prediction in HTTP Transactions

机译:数据挖掘算法在HTTP事务中的TCP吞吐量预测中的应用

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This paper presents a study of the application of data mining algorithms to the prediction of TCP throughput in HTTP transactions. We are using data mining models built on the basis of historic measurements of network performance gathered using WING system. These measurements reflect Web performance as experienced by the end-users located in Wroclaw, Poland. Data mining models are created using the algorithms available in Microsoft SQL Server 2005 and IBM Intelligent Miner tools. Our results show that our data mining based TCP throughput prediction returns accurate results. The application of our method in building of so-called "best performance hit" operation mode of the search engines is proposed.
机译:本文介绍了数据挖掘算法在HTTP事务中预测TCP吞吐量的应用。我们正在使用基于使用翼系统收集的网络性能的历史测量来建立的数据挖掘模型。这些测量反映了位于波兰弗罗茨瓦夫的最终用户所经历的网络性能。使用Microsoft SQL Server 2005和IBM Intelligent Miner Tools中提供的算法创建数据挖掘模型。我们的结果表明,我们基于数据挖掘的TCP吞吐量预测返回准确的结果。提出了我们在建立搜索引擎的所谓“最佳性能击中”操作模式中的建立方法的应用。

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