Evaluations of Web Server Performance with Heavy-tailedness

T. Nakashima
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引用次数: 3

Abstract

Providing quality of service (QoS) in a business environment requires accurate estimation of Internet traffic, especially HTTP traffic. HTTP traffic, mainly consisting of file transmission traffic, depends on the sizes of files with a heavy-tailed property. Analyzing the performance of specific Web servers and comparing server performance is important in QoS provisioning for user applications. In this paper, we present the experimental analysis of Web server performance using our active measurement. We capture activity data from 1984 diverse Web servers by sending measurement packets 20 times in order to evaluate the spatial properties, and we select 14 Web servers to send packets 2, 000 times in 5-second intervals to evaluate the temporal properties. The main contribution of our study is to provide methods of evaluating the temporal and spatial properties on any Web server by measuring from a remote observation host, and to illustrate the current activity of temporal and spatial properties in a series of figures. Crovella's well known work merely describes the self-similar properties for the total transmission time generated by a heavy-tailed file size distribution. We divided the total transmission time into network and server system dependable elements, of which the heavy-tailed properties are captured. We found that temporal properties consist of two factors: stability and activity in the Poisson process. Robustness of heavy-tailedness in terms of constructing elements of total transmission time was evident from the analysis of spatial properties. Finally, we observed the upper boundary and classified groups in a mean-variance plot of primitive elements of the Web server.
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重载Web服务器性能评估
在业务环境中提供服务质量(QoS)需要准确估计Internet流量,特别是HTTP流量。HTTP流量主要由文件传输流量组成,依赖于具有重尾属性的文件大小。在为用户应用程序提供QoS时,分析特定Web服务器的性能并比较服务器性能非常重要。在本文中,我们使用我们的主动测量方法对Web服务器性能进行了实验分析。我们从1984个不同的Web服务器捕获活动数据,通过发送20次测量数据包来评估空间属性,我们选择14个Web服务器在5秒间隔内发送2000次数据包来评估时间属性。本研究的主要贡献在于提供了通过远程观测主机测量任意Web服务器上的时间和空间属性的评估方法,并通过一系列图表说明了时间和空间属性的当前活动。Crovella的著名工作仅仅描述了由重尾文件大小分布产生的总传输时间的自相似性质。将总传输时间划分为网络可靠时间和服务器系统可靠时间两个部分,并捕获了其中的重尾特征。我们发现泊松过程的时间性质由两个因素组成:稳定性和活动性。从空间特性的分析可以看出,在总传输时间的构造要素方面,重尾性的鲁棒性是显而易见的。最后,我们观察了Web服务器原始元素的上边界,并在平均方差图中进行了分类。
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