A Measurement of Mobile Traffic Offloading

  • Kensuke Fukuda
  • Kenichi Nagami
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7799)


A promising way to use limited 3G mobile resources efficiently is 3G mobile traffic offloading through WiFi by the user side. However, we currently do not know enough about how effective the mobile traffic offloading is in the wild. In this paper, we report the results of a two-day-long user-based measurement of mobile traffic offloading by over 400 android smartphone users in Japan. We first explain that the variation of aggregated traffic volume via WiFi is much greater than that via 3G in our dataset. Next, we show that the traffic volume offloading through WiFi is common over whole weekend and weekday night, though weekday rush hours have less chance of traffic offloading. Our results emphasize that a small fraction of users contribute to a large fraction of offload traffic volume. In fact, our per-user level analysis reveals that the top 30% of users downloaded over 90% of their total traffic volume via WiFi. However, bottom 20% of users stuck to 3G only and over 50% of users turned off the WiFi interface in business hours. Also, 17.4% of the total traffic volume was generated by users whose WiFi traffic volume was less than 1MB. We observed that some hybrid users downloaded most of their traffic volume via WiFi in shorter durations. In this sense, there is more room to improve the current traffic offloading by promoting users to use WiFi more effectively. Furthermore, we demonstrate that WiFi offloading is mainly performed by access points (APs) in homes while the use of public WiFi APs is still uncommon in our dataset.


Traffic Volume WiFi Network Mobile Traffic WiFi Interface Hybrid User 
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  1. 1.
    Balakrishnan, M., Mohomed, I., Ramasubramanian, V.: Where’s that phone?: Geolocating IP addresses on 3G networks. In: IMC 2009, Chicago, IL, pp. 294–300 (November 2009)Google Scholar
  2. 2.
    Balasubramanian, A., Mahajan, R., Venkataramani, A.: Augmenting mobile 3G using WiFi. In: MobiSys 2010, San Francisco, CA, pp. 209–222 (June 2010)Google Scholar
  3. 3.
    Cho, K., Fukuda, K., Esaki, H., Kato, A.: Observing slow crustal movement in residential user traffic. In: ACM CoNEXT 2008, Madrid, Spain, p. 12 (December 2008)Google Scholar
  4. 4.
    Falaki, H., Mahajan, R., Kandula, S., Lymberopoulos, D., Govindan, R., Estrin, D.: Diversity in smartphone usage. In: MobiSys 2010, San Francisco, CA, pp. 179–194 (June 2010)Google Scholar
  5. 5.
    Gass, R., Diot, C.: An Experimental Performance Comparison of 3G and Wi-Fi. In: Krishnamurthy, A., Plattner, B. (eds.) PAM 2010. LNCS, vol. 6032, pp. 71–80. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  6. 6.
    Gember, A., Anand, A., Akella, A.: A Comparative Study of Handheld and Non-handheld Traffic in Campus Wi-Fi Networks. In: Spring, N., Riley, G.F. (eds.) PAM 2011. LNCS, vol. 6579, pp. 173–183. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Hare, J., Hartung, L., Banerjee, S.: Beyond deployments and testbeds: Experiences with public usage on vehicular WiFi hotspots. In: MobiSys 2012, Low Wood Bay, UK, pp. 393–405 (June 2012)Google Scholar
  8. 8.
    Henderson, T., Kotz, D., Abyzov, I.: The changing usage of a mature campus-wide wireless network. In: MobiCom 2004, Philadelphia, PA, pp. 187–201 (2004)Google Scholar
  9. 9.
    Huang, J., Xu, Q., Tiwana, B., Mao, Z.M., Zhang, M., Bahl, P.: Anatomizing application performance differences on smartphones. In: MobiSys 2010, San Francisco, CA, pp. 165–178 (June 2010)Google Scholar
  10. 10.
    Jang, K., Han, M., Cho, S., Ryu, H.-K., Lee, J., Lee, Y., Moon, S.: 3G and 3.5G wireless network performance measured from moving cars and high-speed trains. In: MICNET 2009, Beijing, China, pp. 19–24 (October 2009)Google Scholar
  11. 11.
    Lee, K., Rhee, I., Lee, J., Chong, S., Yi, Y.: Mobile data offloading: How much can WiFi deliver? In: CoNEXT 2010, Philadelphia, PA, p. 12 (December 2010)Google Scholar
  12. 12.
    Maier, G., Schneider, F., Feldmann, A.: A First Look at Mobile Hand-Held Device Traffic. In: Krishnamurthy, A., Plattner, B. (eds.) PAM 2010. LNCS, vol. 6032, pp. 161–170. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  13. 13.
    Ministry of Internal Affairs and Communications. Growth of Mobile Traffic in Japan (2011),
  14. 14.
    Trestian, I., Ranjan, S., Kuzmanovic, A., Nucci, A.: Measuring serendipity: Connecting people, locations and interests in a mobile 3G network. In: IMC 2009, Chicago, IL, pp. 267–279 (November 2009)Google Scholar
  15. 15.
    Xu, Q., Erman, J., Gerber, A., Mao, Z., Pang, J., Venkataraman, S.: Identifying diverse usage of behaviors of smartphone apps. In: IMC 2011, Berlin, Germany, pp. 329–344 (November 2011)Google Scholar
  16. 16.
    Zhu, Z., Cao, G., Keralapura, R., Nucci, A.: Characterizing data services in a 3G network: Usage, mobility and access issues. In: ICC 2011, Kyoto, p. 6 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kensuke Fukuda
    • 1
  • Kenichi Nagami
    • 2
  1. 1.National Institute of InformaticsJapan
  2. 2.INTEC, IncJapan

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