Measurement-driven mobile data traffic modeling in a large metropolitan area

Abstract : Understanding mobile data traffic demands is crucial to the evaluation of strategies addressing the problem of high bandwidth usage and scalability of network resources, brought by the pervasive era. In this paper, we conduct the first detailed measurement-driven modeling of smartphone subscribers' mobile traffic usage in a metropolitan scenario. We use a large-scale dataset collected inside the core of a major 3G network of Mexico's capital. We first analyse individual subscribers routinary behaviour and observe identical usage patterns on different days. This motivates us to choose one day for studying the subscribers' usage pattern (i.e., "when" and "how much" traffic is generated) in detail. We then classify the subscribers in four distinct profiles according to their usage pattern. We finally model the usage pattern of these four subscriber profiles according to two different journey periods: peak and non-peak hours.We show that the synthetic trace generated by our data traffic model consistently imitates different subscriber profiles in two journey periods, when compared to the original dataset.
Type de document :
Communication dans un congrès
PerCom 2015- 13th Conference on Pervasive Computing and Communications, Mar 2015, St. Louis, Missouri, United States. IEEE, 2014, 〈http://www.percom.org〉
Liste complète des métadonnées

Littérature citée [15 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01089434
Contributeur : Eduardo Mucelli Rezende Oliveira <>
Soumis le : jeudi 12 mars 2015 - 11:43:57
Dernière modification le : mardi 9 janvier 2018 - 13:46:48
Document(s) archivé(s) le : lundi 17 avril 2017 - 09:56:17

Fichier

percom.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01089434, version 1

Collections

Citation

Eduardo Mucelli Rezende Oliveira, Aline Carneiro Viana, Kolar Purushothama Naveen, Carlos Sarraute. Measurement-driven mobile data traffic modeling in a large metropolitan area. PerCom 2015- 13th Conference on Pervasive Computing and Communications, Mar 2015, St. Louis, Missouri, United States. IEEE, 2014, 〈http://www.percom.org〉. 〈hal-01089434〉

Partager

Métriques

Consultations de la notice

377

Téléchargements de fichiers

168