Server Load Prediction on Wikipedia Traffic: Influence of Granularity and Time Window

  • Cláudio A. D. SilvaEmail author
  • Carlos GriloEmail author
  • Catarina SilvaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 942)


Server load prediction has different approaches and applications, with the general goal of predicting future load for a period of time ahead on a given system. Depending on the specific goal, different methodologies can be defined. In this paper, we follow a pre-processing approach based on defining and testing time-windows and granularity using linear regression, ANN and SVM learning models. Results on real data from Wikipedia servers show that it is possible to tune the size of the time-window and the granularity to improve prediction results.


Load forecasting Linear regression Artificial Neural Networks Support Vector Machines Server load prediction Wikipedia 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Technology and ManagementPolytechnic Institute of LeiriaLeiriaPortugal
  2. 2.CIICPolytechnic Institute of LeiriaLeiriaPortugal
  3. 3.Center for Informatics and Systems of the University of CoimbraCoimbraPortugal

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