Breaking for commercials: characterizing mobile advertising

  • Authors:
  • Narseo Vallina-Rodriguez;Jay Shah;Alessandro Finamore;Yan Grunenberger;Konstantina Papagiannaki;Hamed Haddadi;Jon Crowcroft

  • Affiliations:
  • University of Cambridge, Cambridge, United Kingdom;University of Cambridge, Cambridge, United Kingdom;Politecnico di Torino, Torino, Italy;Telefonica Research, Barcelona, Spain;Telefonica Research, Barcelona, Spain;Queen Mary, University of London, London, United Kingdom;University of Cambridge, Cambridge, United Kingdom

  • Venue:
  • Proceedings of the 2012 ACM conference on Internet measurement conference
  • Year:
  • 2012

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Abstract

Mobile phones and tablets can be considered as the first incarnation of the post-PC era. Their explosive adoption rate has been driven by a number of factors, with the most signifcant influence being applications (apps) and app markets. Individuals and organizations are able to develop and publish apps, and the most popular form of monetization is mobile advertising. The mobile advertisement (ad) ecosystem has been the target of prior research, but these works typically focused on a small set of apps or are from a user privacy perspective. In this work we make use of a unique, anonymized data set corresponding to one day of traffic for a major European mobile carrier with more than 3 million subscribers. We further take a principled approach to characterize mobile ad traffic along a number of dimensions, such as overall traffic, frequency, as well as possible implications in terms of energy on a mobile device. Our analysis demonstrates a number of inefficiencies in today's ad delivery. We discuss the benefits of well-known techniques, such as pre-fetching and caching, to limit the energy and network signalling overhead caused by current systems. A prototype implementation on Android devices demonstrates an improvement of 50 % in terms of energy consumption for offline ad-sponsored apps while limiting the amount of ad related traffic.