Energy prediction of access points in Wi-Fi networks according to users' behaviour

David Rodriguez-Lozano, Juan A. Gomez-Pulido, Jose M. Lanza-Gutierrez, Arturo Duran-Dominguez, BRODERICK CRAWFORD LABRIN, RICARDO JAVIER SOTO DE GIORGIS

Research output: Contribution to journalArticlepeer-review

Abstract

Some maintenance tasks in Wi-Fi networks may involve removing an access point due to several reasons. As a result, the new infrastructure registers a different number of roamings in the access points according to the users' behaviour, with a certain energy impact added to the consumption caused by the own operations of the devices. This energy effect should be understood in order to tackle the measures aimed at planning the infrastructure deployment. In this work, we propose a methodology to predict the energy consumption in the access points of a Wi-Fi network when we remove a particular device, based on a twofold support. We predict the number of roamings following a method previously validated; on the other hand, we assess the relationship between roamings and energy in the full infrastructure, using the data collected from a high number of network users during a given time in order to reflect the users' behaviour with the maximum accuracy. From this knowledge, we can infer the energy prediction for a different environment where the roamings are predicted using techniques based on recommender systems and machine learning.

Original languageEnglish
Article number825
JournalApplied Sciences (Switzerland)
Volume7
Issue number8
DOIs
StatePublished - 11 Aug 2017

Keywords

  • Access point
  • Energy
  • Prediction
  • Recommender systems
  • Roamings
  • Wi-Fi networks

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