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Web Server Loads under Visitor Surges : A Model-Based Prediction

Bouma, G (2021) Web Server Loads under Visitor Surges : A Model-Based Prediction.

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Abstract:Cognito Concepts is a marketing agency that also hosts websites for most of their clients. They struggle with distributing these websites in a balanced way over multiple webservers. Since some websites only have seasonal visitors and are heavily influenced by markerting campaigns they do not have a steady load throughout the year. To make optimum use of the webservers it is necessary to fairly accurate predict the load a website will have on a webserver. The webservers allow to log measurements that give us a good insight into CPU, RAM memory and network usage. As well as to which pages are requested, in which order, how long they took to be processed and how long it took for the next page to be requested. This data is processed from the log files and put into a database to make it possible to easily fetch data from a specific date, time, site and/or page. From the selected data different model variants can be generated for the Modest toolset. Modest makes it relatively easy to fit this data into Markov automata to simulate visitor behavior. Then influence it with data for planned marketing campaigns to predict its impact. Having these models gave some extra insights such as the possibility to solve questions as how long it would take for a server to recover from an overload under normal conditions. The results showed that we could do a near perfect simulation of actual scenarios. A prediction was a bit more tricky and was a bit off. There are still some more areas to investigate to improve accuracy. But in the end the predictions and new possibilities look promising
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science MSc (60300)
Link to this item:http://purl.utwente.nl/essays/86067
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