Skip to main content
SpringerLink
Log in

WGM: Wavelet-Based Gamma Model for Video Traffic in Wireless Multi-hop Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

While most of the existing literature concentrates on wireless traffic characterization and its effects on network performance, relatively little research work has focused on mathematical modeling and queuing analysis of video traffic in wireless multi-hop networks. The purpose of this paper is to characterize and model wireless multi-hop network video traffic. We begin with thorough analysis and investigations of characteristics of video traffic in typical wireless network scenarios, building upon which we present a novel Wavelet-based Gamma Model (WGM) for wireless multi-hop video streaming. Our analytic and simulation results demonstrate that the WGM provides a flexible and robust means to characterize wireless video traffic, in terms of statistical properties and self-similarity. On this basis, a WGM queuing system is constructed to deduce the theoretical value of buffer overflow probability, delay and delay jitter for wireless media streaming. A series of simulation experiments are conducted to demonstrate the generality and effectiveness of our modeling approach. Our experimental results show that the probability of buffer overflow indicates a hyperbolic decay as the buffer size increases; however, the buffer overflow probability decays exponentially fast, as the sending rate increases. The study also finds that, as the buffer size increases, the delay and delay jitter of video streaming first increase then become stable, but with an increase in the sending rate, both values decrease sharply. We believe that this conclusion could contribute to the design of appropriate network architectures and to elaborate efficient wireless multimedia communication protocols.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Ericsson, A. B. (2017). Ericsson mobility report: On the pulse of the networked society. Ericsson, Sweden, Tech. Rep. EAB-17.

  2. Fontugne, R., Abry, P., Fukuda, K., Veitch, D., Cho, K., Borgnat, P., et al. (2017). Scaling in internet traffic: A 14 year and 3 day longitudinal study, with multiscale analyses and random projections. IEEE/ACM Transactions on Networking, 25(4), 2152–2165.

    Article  Google Scholar 

  3. Chaurasia, A., & Sehgal, V. K. (2015). Optimal buffer-size by synthetic self-similar traces for different traffics for NoC. SIGBED Reviev, 12(3), 6–12.

    Article  Google Scholar 

  4. Min, G., & Jin, X. (2013). Analytical modelling and optimization of congestion control for prioritized multi-class self-similar traffic. IEEE Transactions on Communications, 61(1), 257–265.

    Article  Google Scholar 

  5. Lin, S.-C., Wang, P., Akyildiz, I. F., & Luo, M. (2016). Throughput-optimal LIFO policy for bounded delay in the presence of heavy-tailed traffic. In Proceedings of IEEE GLOBECOM (pp. 1–7).

  6. Wang, P., & Akyildiz, I. F. (2015). On the stability of dynamic spectrum access networks in the presence of heavy tails. IEEE Transactions on Wireless Communications, 14(2), 870–881.

    Article  Google Scholar 

  7. Kalbkhani, H., Shayesteh, M. G., & Haghighat, N. (2017). Adaptive lstar model for long-range variable bit rate video traffic prediction. IEEE Transactions on Multimedia, 19(5), 999–1014.

    Article  Google Scholar 

  8. Kastrinakis, M., Badawy, G., Smadi, M. N., & Koutsakis, P. (2017). Video frame size modeling for user-generated traffic in an enterprise-like environment. Computer Communications, 109(5), 24–37.

    Article  Google Scholar 

  9. Toral-Cruz, H., Pathan, A.-S. K., & Pacheco, J. C. R. (2013). Accurate modeling of voip traffic qos parameters in current and future networks with multifractal and Markov models. Mathematical and Computer Modelling, 57(11), 2832–2845.

    Article  MathSciNet  MATH  Google Scholar 

  10. Jin, X., & Min, G. (2007). Performance modelling of priority queuing discipline under self-similar and poisson traffic. In Proceedings of IEEE LCN (pp. 567–574).

  11. Adas, A. (1997). Traffic models in broadband networks. IEEE Communications Magazine, 35(7), 82–89.

    Article  Google Scholar 

  12. Willinger, W., Taqqu, M. S., Sherman, R., & Wilson, D. V. (1997). Self-similarity through high-variability: Statistical analysis of ethernet lan traffic at the source level. IEEE/ACM Transactions on Networking, 5(1), 71–86.

    Article  Google Scholar 

  13. Yang, X., & Petropulu, A. P. (2001). The extended alternating fractal renewal process for modeling traffic in high-speed communication networks. IEEE Transactions on Signal Processing, 49(7), 1349–1363.

    Article  Google Scholar 

  14. Mandelbrot, B. B., & Van Ness, J. W. (1968). Fractional brownian motions, fractional noises and applications. SIAM Review, 10(4), 422–437.

    Article  MathSciNet  MATH  Google Scholar 

  15. Hosking, J. R. M. (1981). Fractional differencing. Biometrika, 68(1), 165–176.

    Article  MathSciNet  MATH  Google Scholar 

  16. Girma, D., Lazaro, O., & Dunlop, J. (2000). Online video traffic modelling with wavelet transform. Electronics Letters, 36(16), 1368–1370.

    Article  Google Scholar 

  17. Wang, P., & Akyildiz, I. F. (2011). Spatial correlation and mobility-aware traffic modeling for wireless sensor networks. IEEE/ACM Transactions on Networking, 19(6), 1860–1873.

    Article  Google Scholar 

  18. Jin, X., & Min, G. (2009). Modelling and analysis of priority queueing systems with multi-class self-similar network traffic: A novel and efficient queue-decomposition approach. IEEE Transactions on Communications, 57(5), 1444–1452.

    Article  Google Scholar 

  19. Ghosh, A., Jana, R., Ramaswami, V., Rowland, J., & Shankaranarayanan, N. K. (2011). Modeling and characterization of large-scale wi-fi traffic in public hot-spots. In Proceedings of IEEE INFOCOM (pp. 2921–2929).

  20. Ma, S., & Ji, C. (1998). Modeling video traffic in the wavelet domain. In Proceedings of IEEE INFOCOM (pp. 201–208).

  21. Leland, W. E., Taqqu, M. S., Willinger, W., & Wilson, D. V. (1994). On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Transactions on Networking, 2(1), 1–15.

    Article  Google Scholar 

  22. Crovella, M. E., & Bestavros, A. (1997). Self-similarity in world wide web traffic: Evidence and possible causes. IEEE/ACM Transactions on Networking, 5(6), 835–846.

    Article  Google Scholar 

  23. Bai, G., & Williamson, C. (2004). Time-domain analysis of web cache filter effects. Performance Evaluation, 58(2), 285–317.

    Article  Google Scholar 

  24. Sahinoglu, Z., & Tekinay, S. (1999). On multimedia networks: Self-similar traffic and network performance. IEEE Communications Magazine, 37(1), 48–52.

    Article  Google Scholar 

  25. Karagiannis, T., Molle, M., Faloutsos, M., & Broido, A. (2004). A nonstationary Poisson view of internet traffic. In Proceedings of INFOCOM (pp. 1558–1569).

  26. Borgnat, P., Dewaele, G., Fukuda, K., Abry, P., & Cho, K. (2009). Seven years and one day: Sketching the evolution of internet traffic. In Proceedings of INFOCOM (pp. 711–719).

  27. Yin, S., & Lin, X. (2005). Traffic self-similarity in mobile ad hoc networks. In Proceedings of IFIP WOCN (pp. 285–289).

  28. Tickoo, O., & Sikdar, B. (2003). On the impact of IEEE 802.11 mac on traffic characteristics. IEEE Journal on Selected Areas in Communications, 21(2), 189–203.

    Article  Google Scholar 

  29. Oliveira, C., Kim, J. B., & Suda, T. (2003). Long-range dependence in IEEE 802.11 b wireless LAN traffic: An empirical study. In Proceedings of IEEE CCW (pp. 17–23).

  30. Jie, Y., & Petropulu, A. P. (2006). Study of the effect of the wireless gateway on incoming self-similar traffic. IEEE Transactions on Signal Processing, 54(10), 3741–3758.

    Article  MATH  Google Scholar 

  31. Ge, X., Yang, Y., Wang, C.-X., Liu, Y.-Z., Liu, C., & Xiang, L. (2010). Characteristics analysis and modeling of frame traffic in 802.11 wireless networks. Wireless Communications and Mobile Computing, 10(4), 584–592.

    Google Scholar 

  32. Li, X., Lu, H., & Lu, H. (2013). QoS analysis of self-similar multimedia traffic with variable packet size in wireless networks. In Proceedings of VTC Fall (pp. 1–5).

  33. Tewfik, A. H., & Kim, M. (1992). Correlation structure of the discrete wavelet coefficients of fractional brownian motion. IEEE Transactions on Information Theory, 38(2), 904–909.

    Article  MathSciNet  MATH  Google Scholar 

  34. Ribeiro, V. J., Riedi, R. H., Crouse, M. S., & Baraniuk, R. G. (2000). Multiscale queuing analysis of long-range-dependent network traffic. In Proceedings of IEEE INFOCOM (pp. 1026–1035).

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant Nos. 61502230 and 61073197, in part by the Natural Science Foundation of Jiangsu Province under Grant No. BK20150960, in part by the National Key R&D Program of China under Grant No. 2018YFC0808500, in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant No. 15KJB520015, in part by the National Engineering Research Center Program of Communications and Networking under Grant No. GCZX012, in part by the Nanjing Municipal Science and Technology Plan Project under Grant No. 201608009. The first author is especially grateful to the Jiangsu Government Scholarship for Overseas Studies assisting his research abroad.

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Nanjing Tech University, No. 30, PuZhu Road (South), Pukou District, Nanjing, 211816, Jiangsu Province, China

    Hang Shen, Guangwei Bai, Junyuan Wang & Lu Zhao

  2. National Engineering Research Center of Communications and Networking (Nanjing University of Posts and Telecommunications), Nanjing, 210003, China

    Hang Shen

Authors
  1. Hang Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guangwei Bai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junyuan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lu Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guangwei Bai.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shen, H., Bai, G., Wang, J. et al. WGM: Wavelet-Based Gamma Model for Video Traffic in Wireless Multi-hop Networks. Wireless Pers Commun 107, 565–587 (2019). https://doi.org/10.1007/s11277-019-06289-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-06289-y

Keywords

Search

Navigation