Advertisement

Mobile Network Performance from User Devices: A Longitudinal, Multidimensional Analysis

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8362)

Abstract

In the cellular environment, operators, researchers and end users have poor visibility into network performance for devices. Improving visibility is challenging because this performance depends factors that include carrier, access technology, signal strength, geographic location and time. Addressing this requires longitudinal, continuous and large-scale measurements from a diverse set of mobile devices and networks.

This paper takes a first look at cellular network performance from this perspective, using 17 months of data collected from devices located throughout the world. We show that (i) there is significant variance in key performance metrics both within and across carriers; (ii) this variance is at best only partially explained by regional and time-of-day patterns; (iii) the stability of network performance varies substantially among carriers. Further, we use the dataset to diagnose the causes behind observed performance problems and identify additional measurements that will improve our ability to reason about mobile network behavior.

Keywords

Mobile Device Packet Loss Signal Strength Network Performance Access Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Sommers, J., Barford, P.: Cell vs. WiFi: on the performance of metro area mobile connections. In: Proc. ACM SIGCOMM IMC (2012)Google Scholar
  2. 2.
    Tan, W.L., Lam, F., Lau, W.C.: An Empirical Study on 3G Network Capacity and Performance. In: Proc. IEEE INFOCOM (2007)Google Scholar
  3. 3.
    Huang, J., Xu, Q., Tiwana, B., Mao, Z.M., Zhang, M., Bahl, P.: Anatomizing application performance differences on smartphones. In: Proc. ACM MOBISYS (2010)Google Scholar
  4. 4.
    Liu, X., Sridharan, A., Machiraju, S., Seshadri, M., Zang, H.: Experiences in a 3G network: interplay between the wireless channel and applications. In: Proc. ACM MOBICOM (2008)Google Scholar
  5. 5.
    Jurvansuu, M., Prokkola, J., Hanski, M., Perala, P.: HSDPA Performance in Live Networks. In: IEEE ICC (2007)Google Scholar
  6. 6.
    Laner, M., Svoboda, P., Romirer-Maierhofer, P., Nikaein, N., Ricciato, F., Rupp, M.: A comparison between one-way delays in operating HSPA and LTE networks. In: Proc. WINMEE (2012)Google Scholar
  7. 7.
    Vacirca, F., Ricciato, F., Pilz, R.: Large-Scale RTT Measurements from an Operational UMTS/GPRS Network. In: WICON (2005)Google Scholar
  8. 8.
    Laner, M., Svoboda, P., Hasenleithner, E., Rupp, M.: Dissecting 3G Uplink Delay by Measuring in an Operational HSPA Network. In: Spring, N., Riley, G.F. (eds.) PAM 2011. LNCS, vol. 6579, pp. 52–61. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  9. 9.
    Romirer-Maierhofer, P., Ricciato, F., D’Alconzo, A., Franzan, R., Karner, W.: Network-Wide Measurements of TCP RTT in 3G. In: Papadopouli, M., Owezarski, P., Pras, A. (eds.) TMA 2009. LNCS, vol. 5537, pp. 17–25. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Deshpande, P., Hou, X., Das, S.R.: Performance Comparison of 3G and Metro-Scale WiFi for Vehicular Network Access. In: Proc. ACM SIGCOMM IMC (2010)Google Scholar
  11. 11.
    Elmokashfi, A., Kvalbein, A., Xiang, J., Evensen, K.R.: Characterizing delays in norwegian 3G networks. In: Taft, N., Ricciato, F. (eds.) PAM 2012. LNCS, vol. 7192, pp. 136–146. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  12. 12.
    Zheng, H., Lua, E.K., Pias, M., Griffin, T.G.: Internet routing policies and round-trip-times. In: Dovrolis, C. (ed.) PAM 2005. LNCS, vol. 3431, pp. 236–250. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  13. 13.
    Huang, J., Qian, F., Guo, Y., Zhou, Y., Xu, Q., Mao, Z.M., Sen, S., Spatscheck, O.: An in-depth study of lte: Effect of network protocol and application behavior on performance. In: Proc. ACM SIGCOMM (2013)Google Scholar
  14. 14.
    Zarifis, K., Flach, T., Nori, S., Choffnes, D., Govindan, R., Katz-Bassett, E., Mao, Z.M., Welsh, M.: Diagnosing path inflation of mobile client traffic. In: Faloutsos, M., Kuzmanovic, A. (eds.) PAM 2014. LNCS, vol. 8362, pp. 21–30. Springer, Heidelberg (2014)Google Scholar
  15. 15.
    Schulman, A., Navday, V., Ramjeey, R., Spring, N., Deshpandez, P., Grunewald, C., Padmanabhany, K.J.V.N.: Bartendr: A practical approach to energy-aware cellular data scheduling. In: Proc. ACM MOBICOM (2010)Google Scholar
  16. 16.
    Lee, Y.: Measured TCP Performance in CDMA 1x EV-DO Network. In: Proc. PAM (2006)Google Scholar
  17. 17.
    Claypool, M., Kinicki, R., Lee, W., Li, M., Ratner, G.: Characterization by Measurement of a CDMA 1x EVDO Network. In: Proc. WICON (2006)Google Scholar
  18. 18.
    Mattar, K., Sridharan, A., Zang, H., Matta, I., Bestavros, A.: TCP over CDMA2000 networks: A cross-layer measurement study. In: Uhlig, S., Papagiannaki, K., Bonaventure, O. (eds.) PAM 2007. LNCS, vol. 4427, pp. 94–104. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  19. 19.
    Arlos, P., Fiedler, M.: Influence of the Packet Size on the One-Way Delay in 3G Networks. In: Krishnamurthy, A., Plattner, B. (eds.) PAM 2010. LNCS, vol. 6032, pp. 61–70. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.University of MichiganUSA
  2. 2.Northeastern UniversityUSA
  3. 3.University of Southern CaliforniaUSA
  4. 4.Google Inc.USA

Personalised recommendations