Time Is Perception Is Money – Web Response Times in Mobile Networks with Application to Quality of Experience

  • Markus Fiedler
  • Patrik Arlos
  • Timothy A. Gonsalves
  • Anuraag Bhardwaj
  • Hans Nottehed
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6821)


The number of mobile operators providing Internet access to end users is growing. However, irrespective of the access network, we observe a distinct sensitivity of user perception to response and download times, in particular for interactive services on the web. In order to facilitate the choice of the right network for a given task, this paper presents a systematic study of web download time and corresponding throughput as a function of the file size. Based on measurement data from three Swedish mobile operators and a particular strategy of choosing file sizes, we find surprisingly simple, yet sufficiently accurate approximations of download times. These approximations are based on simple-to-measure parameters and provide valuable quantitative insights into the acceleration of HTTP/TCP/IP-based data delivery. The paper discusses the emergence of these approximations and related errors. Furthermore, it correlates the findings with Quality of Experience, thus building bridges between performance, user perception and provisioning issues.


Download time interactive service web service throughput user perception file size measurements Quality of Experience 


  1. 1.
    Info24, Homepage, (last seen July 31, 2010)
  2. 2.
    ITU-T Recommendation P.10/G.100 (incl. Amendment 2), Vocabulary for performance and quality of service (July 2006) (2008)Google Scholar
  3. 3.
    Shaikh, J., Fiedler, M., Collange, D.: Quality of Experience from user and network perspectives. Annals of Telecommunications, Special Issue on Quality of Experience: 1/Metrics and Performance Evaluation 65(1-2) (January-February 2010), electronically available at, doi:10.1007/s12243-009-0142-x
  4. 4.
    Gonsalves, T., Bhardwaj, A.: Comparison of AT-Tester with other popular testers for Quality of Service Experience (QoSE) of an internet connection (August 2009),
  5. 5.
    Mellia, M., Stoica, I., Zhang, H.: TCP model for short lived flows. IEEE Comm. Letters 6(2), 85–87 (2002)CrossRefGoogle Scholar
  6. 6.
    Chakravorty, R., Pratt, I.: WWW performance over GPRS. In: Proc. 4th Int. Workshop on Mobile and Wireless Communication Networks (MWCN 2002), pp. 527–531 (September 2002)Google Scholar
  7. 7.
    Zona Research Inc., “The economic impacts of unacceptable web-site download speeds,” Report (1999)Google Scholar
  8. 8.
    Nielsen, J.: Usability Engineering. Morgan Kaufman (1994)Google Scholar
  9. 9.
    Rose, G.M., Evaristo, R., Straub, D.: Culture and consumer responses to web download time: a four-continent study of mono and polochronism. IEEE Trans. on Engineering Management 50(1), 31–44 (2003)CrossRefGoogle Scholar
  10. 10.
    ITU-T Recommendation G.1030, Estimating end-to-end performance in IP networks for data applications (November 2005)Google Scholar
  11. 11.
    Fiedler, M., Hoßfeld, T., Tran-Gia, P.: A generic quantitative relationship between Quality of Experience and Quality of Service. IEEE Network, Special Issue on Improving Quality of Experience for Network Services (2), 36–41 (2010)Google Scholar
  12. 12.
    Fiedler, M., Hoßfeld, T.: Quality of Experience-related differential equations and provisioning-delivery hysteresis. In: Proc. 21st ITC Specialist Seminar on Multimedia Applications, Miyazaki, Japan (March 2010),
  13. 13.
    Hoßfeld, T., Tran-Gia, P., Fiedler, M.: Quantification of Quality of Experience for Edge-Based Applications. In: Mason, L.G., Drwiega, T., Yan, J. (eds.) ITC 2007. LNCS, vol. 4516, pp. 361–373. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  14. 14.
    Chen, X., Wang, W., Nie, J.: Analysis of web response time in asymmetrical wireless network. In: Proc. 11th IEEE Singapore Int. Conf. on Communication Systems (ICCS 2008), pp. 1427–1430 (November 2008)Google Scholar
  15. 15.
    Miyagi, M., Ohkubo, K., Kataoka, M., Yoshizawa, S.: Performance prediction method for web-access response time distribution using formula. In: Proc. IEEE/IFIP Network Operations and Management Symposium (NOMS 2004), vol. 1, pp. 905–906 (April 2004)Google Scholar
  16. 16.
    Chan, M.C., Ramjee, R.: TCP/IP performance over 3G wireless links with rate and delay variation. In: MobiCom 2002: Proc. of the 8th Annual International Conference on Mobile Computing and Networking, pp. 71–82. ACM, New York (2002)CrossRefGoogle Scholar
  17. 17.
    Voskarides, S., et al.: Practical evaluation of GPRS use in telemedicine system in Cyprus. In: Proc. 4th Int. IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine, pp. 39–42 (April 2003)Google Scholar
  18. 18.
    Baccarelli, E., Biagi, M., Cordeschi, N., Pelizzoni, C.: Minimization of download times of large files over wireless channels. IEEE Trans. on Mobile Computing 6(10), 1105–1115 (2007)CrossRefGoogle Scholar
  19. 19.
    Arlos, P., Fiedler, M.: Influence of the packet size on the one-way delay on the down-link in 3G networks. In: Proc. ISWPC 2010, Modena, Italy (May 2010)Google Scholar
  20. 20.
    Reichl, P., Egger, S., Schatz, R., d’Alconzo, A.: The logarithmic nature of QoE and the role of the Weber-Fechner Law in QoE assessment. In: Proc. IEEE ICC 2010, Cape Town, South Africa (May 2010)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Markus Fiedler
    • 1
  • Patrik Arlos
    • 1
  • Timothy A. Gonsalves
    • 2
  • Anuraag Bhardwaj
    • 1
    • 3
  • Hans Nottehed
    • 4
  1. 1.Blekinge Institute of TechnologyKarlskronaSweden
  2. 2.Indian Institute of Technology MandiIndia
  3. 3.Indian Institute of Technology MadrasChennaiIndia
  4. 4.info24KistaSweden

Personalised recommendations