Title page for ETD etd-041608-135533

Document Type thesis

Author Name Ma, Chunling

Email Address horsie at gmail dot com

URN etd-041608-135533

Title Using Network Application Behavior to Predict Performance

Degree MS

Department Computer Science

Advisors
Craig E. Wills, Advisor
Robert E. Kinicki, Reader

Keywords
Network Performance
Prediction
Measurements
Network Metrics

Date of Presentation/Defense 2008-04-07

Availability unrestricted

Abstract
Today`s continuously growing Internet requires users and network applications to have knowledge of network metrics. This knowledge is critical for decision making during the usage of network applications. This thesis studies application related network metrics. The major approach in this work is to examine the traffic between a simulated user and network applications. We use the historical data collected from previous usage of network applications to make predictions for future usage of those applications. We also use the historical data obtained from a given application to make predictions about another application. Prediction mechanisms require us to make parameter choices so that certain weights can be placed on historical data versus current data. We study these different choices and use the values from our best experimental results. From these studies we conclude that our data prediction is quite accurate and remains stable over a range of parameter choices. The use of shared routing paths between users and network applications are explored in the performance prediction of applications. Only some servers at the same locations show similar prediction results. The network applications studied are also varied, including web, streaming, DNS, etc. We see whether sharing information obtained from different applications can be used to make predictions of application performance. However, we observe limited success in predictions across applications.

Files
horsie.pdf

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Document Type	thesis
Author Name	Ma, Chunling
Email Address	horsie at gmail dot com
URN	etd-041608-135533
Title	Using Network Application Behavior to Predict Performance
Degree	MS
Department	Computer Science
Advisors	Craig E. Wills, Advisor Robert E. Kinicki, Reader
Keywords	Network Performance Prediction Measurements Network Metrics
Date of Presentation/Defense	2008-04-07
Availability	unrestricted
Abstract Today`s continuously growing Internet requires users and network applications to have knowledge of network metrics. This knowledge is critical for decision making during the usage of network applications. This thesis studies application related network metrics. The major approach in this work is to examine the traffic between a simulated user and network applications. We use the historical data collected from previous usage of network applications to make predictions for future usage of those applications. We also use the historical data obtained from a given application to make predictions about another application. Prediction mechanisms require us to make parameter choices so that certain weights can be placed on historical data versus current data. We study these different choices and use the values from our best experimental results. From these studies we conclude that our data prediction is quite accurate and remains stable over a range of parameter choices. The use of shared routing paths between users and network applications are explored in the performance prediction of applications. Only some servers at the same locations show similar prediction results. The network applications studied are also varied, including web, streaming, DNS, etc. We see whether sharing information obtained from different applications can be used to make predictions of application performance. However, we observe limited success in predictions across applications.
Files	horsie.pdf