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Spatial Internet Traffic Load Forecasting with Using Estimation Method
Author(s) -
Anna Kamińska-Chuchmała
Publication year - 2014
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2014.08.109
Subject(s) - computer science , download , the internet , kriging , resource (disambiguation) , server , real time computing , data mining , computer network , machine learning , world wide web
Internet traffic is one of the most unpredictable and fluctuating phenomenon to forecast, although accurate prediction is difficult challenge. Many research about measurement experiments are dedicated to predict the performance of Internet network. Especially, during last years this issue is important, when growing demand on reliable access to the Internet is desired by users. In this paper spatial (temporal-area) Internet traffic load forecasting is proposed. Data are obtained from conducted active measurement experiment. Period of time from which is contained database amounts three weeks of October 2013 and each day at the same time at: 06:00 am, 12:00 pm, 06:00 pm and 12:00 am the data were collected. This experiment relies on download a copy of the same resource from servers located in Europe by Wrocław agent. One of the most interesting variable obtained from this experiment is total download time of indicated resource. On basis of this experiment, the Internet traffic forecasts with one week ahead are performed. Spatial forecasting is made by using geostatistical estimation method - ordinary kriging. Paper contains description of ordinary kriging method and preliminary measurement data analysis. Next, model of forecast with discussion of results are given. The final view of performance considered the Internet network in Europe ending the paper

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