access icon free Internet traffic modelling: from superposition to scaling

Internet traffic at various tiers of service providers is essentially a superposition or active mixture of traffic from various sources. Statistical properties of this superposition and a resulting phenomenon of scaling are important for network performance (queuing), traffic engineering (routing) and network dimensioning (bandwidth provisioning). In this article, the authors study the process of superposition and scaling jointly in a non-asymptotic framework so as to better understand the point process nature of cumulative input traffic process arriving at telecommunication devices (e.g., switches, routers). The authors further assess the scaling dynamics of the structural components (packets, flows and sessions) of the cumulative input process and their relation with superposition of point processes. Classical and new results are discussed with their applicability in access and core networks. The authors propose that renewal theory-based approximate point process models, that is, Pareto renewal process superposition and Weibull renewal process superposition can model the similar second-order scaling, as observed in traffic data of access and backbone core networks, respectively.

Inspec keywords: Internet; Weibull distribution; queueing theory; telecommunication network routing; statistical analysis; telecommunication traffic; Pareto distribution

Other keywords: cumulative input process; point process; network dimensioning; scaling dynamics; network performance; nonasymptotic framework; structural components; scaling phenomenon; service provider tiers; switch device; Pareto renewal process superposition; bandwidth provisioning; traffic data; packet component; active traffic mixture; telecommunication network routing; statistical properties; session component; Internet traffic modelling; renewal theory-based approximate point process models; queuing; traffic engineering; telecommunication devices; Weibull renewal process superposition; flow component; traffic superposition; second-order scaling; router device; point process superposition; cumulative input traffic process

Subjects: Queueing theory; Computer communications; Communication network design, planning and routing; Queueing theory; Other computer networks

References

    1. 1)
      • 4. Çinlar, E.: ‘Superposition of point processes’. in Lewis, P.A.W. (Eds.): ‘Stochastic Point Processes: Statistical analysis, theory and applications’ (Wiley series in Probability and Mathematical Statistics, Wiley, 1972), pp. 549606.
    2. 2)
    3. 3)
      • 15. Arfeen, M., Pawlikowski, K., McNickle, D., Willig, A.: ‘Towards a combined traffic modeling framework for access and core networks’. Australasian Telecommunication Networks and Applications Conf. (ATNAC), November 2012, pp. 17.
    4. 4)
    5. 5)
    6. 6)
      • 8. Zhang, Z.-L., Ribeiro, V., Moon, S., Diot, C.: ‘Small-time scaling behaviors of internet backbone traffic: an empirical study’. 22nd Annual Joint Conf. IEEE Computer and Communications (INFOCOM 2003), 2003, pp. 18261836.
    7. 7)
      • 1. Cao, J., Cleveland, W.S., Lin, D., Sun, D.X.: ‘On the nonstationarity of internet traffic’. Proc. 2001 ACM SIGMETRICS Int. Conf. Measurement and Modeling of Computer Systems, New York, NY, USA, 2001, pp. 102112.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
      • 4. Çinlar, E.: ‘Superposition of point processes’. in Lewis, P.A.W. (Eds.): ‘Stochastic Point Processes: Statistical analysis, theory and applications’ (Wiley series in Probability and Mathematical Statistics, Wiley, 1972), pp. 549606.
    13. 13)
      • 26. Beran, J., Feng, Y., Ghosh, S., Kulik, K.: ‘Limit theorems’, in (Ed.): ‘Long-memory processes probabilistic properties and statistical methods’ (Springer, 2013), pp. 356360.
    14. 14)
      • 20. Kaj, I., Taqqu, M.S.: ‘Convergence to fractional Brownian motion and to the telecom process: the integral representation approach’, in Sido-ravicius, V., Vares, M.E. (Eds.): ‘In and out of equilibrium 2’ (Birkhuser Basel, 2008), (of Progress in Probability, 60), pp. 383427.
    15. 15)
    16. 16)
      • 3. Cox, D.R., Smith, W.L.: ‘On the superposition of renewal processes’, Biometrika, 1954, 41, pp. 9199, Biometrika Trust.
    17. 17)
    18. 18)
      • 25. Gordon, J.: ‘Long range correlation in multiplexed Pareto traffic’. Proc. Int. IFIP-IEEE Conf. Global Infrastructure for the Information Age, Broadband Communications, 1996, pp. 2839.
    19. 19)
    20. 20)
      • 9. Karagiannis, T., Molle, M., Faloutsos, M., Broido, A.: ‘A nonstationary Poisson view of internet traffic’. INFOCOM 2004, 2004, vol. 3, pp. 15581569.
    21. 21)
      • 12. Fishman, G.S.: ‘Principles of discrete event simulation’ (John Wiley & Sons, Inc., New York, NY, USA, 1978).
    22. 22)
    23. 23)
      • 27. Arfeen, M.A., Pawlikowski, K., McNickle, D., Willig, A.: ‘The role of the Weibull distribution in internet traffic modeling’. 25th Int. Teletraffic Congress (ITC 2013), Shanghai, People's Republic of China, September 2013.
    24. 24)
      • 32. Ricciato, F., Coluccia, A., D'Alconzo, A., Veitch, D., Borgnat, P., Abry, P.: ‘On the role of flows and sessions in internet traffic modeling: an explorative toy-model’. IEEE Global Telecommunications Conference (GLOBECOM) 2009, December 2009, pp. 18.
    25. 25)
      • 21. Kaj, I.: ‘Convergence of scaled renewal processes to fractional Brownian motion’, Preprint: Department of Mathematics, Uppsala University, Box, vol. 480, 1999.
    26. 26)
    27. 27)
      • 30. Tian, X., Wu, H., Ji, C.: ‘A unified framework for understanding network traffic using independent wavelet models’. IEEE Proc. 21st Annual Joint Conf. IEEE Computer and Communications Societies (INFOCOM 2002), 2002, vol. 1, pp. 446454.
    28. 28)
      • 2. Veitch, D., Hohn, N., Abry, P.: ‘Multifractality in TCP/IP traffic: the case against’, Comput. Netw., Spec. Issue ‘Long-Range Depend. Traffic’, 2005, 48, pp. 293313.
    29. 29)
      • 14. Daley, D.J., Vere-Jones, D.: ‘An introduction to the theory of point processes. Vol. II’, in ‘Probability and its applications (New York)’ (Springer, New York, 2008, 2nd edn.), General theory and structure.
    30. 30)
      • 17. Hohn, N., Veitch, D., Abry, P.: ‘Does fractal scaling at the IP level depend on TCP flow arrival processes?’. Proc. ACM SIGCOMM Internet Measurement Workshop (IMW-2002), Marseille, 6–8 November 2002, pp. 6368.
    31. 31)
    32. 32)
      • 6. Cao, J., Cleveland, W., Lin, D., Sun, D.: ‘Internet traffic tends toward Poisson and independent as the load increases’, in Denison, D., Hansen, M., Holmes, C., Mallick, B., Yu, B. (Eds.): ‘Nonlinear estimation and classification’ (Springer, New York, 2003), (Lecture Notes in Statistics, 171), pp. 83109.
    33. 33)
    34. 34)
      • 33. Veitch, D.: ‘Scale invariance in computer network traffic’ (ISTE, 2010), pp. 413436.
    35. 35)
      • 16. Janevski, N., Goseva-Popstojanova, K.: ‘Accounting for characteristics of session work-loads: a study based on partly-open queue’. Int. Conf.Communications (ICC), June 2012, pp. 447452.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-net.2013.0148
Loading

Related content

content/journals/10.1049/iet-net.2013.0148
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading