Abstract
Identifying the statistical properties of the Interdomain Traffic Matrix (ITM) is fundamental for Internet techno-economic studies but challenging due to the lack of adequate traffic data. In this work, we utilize a Europe-wide measurement infrastructure deployed at the GÉANT backbone network to examine some important spatial properties of the ITM. In particular, we analyze its sparsity and characterize the distribution of traffic generated by different ASes. Our study reveals that the ITM is sparse and that the traffic sent by an AS can be modeled as the LogNormal or Pareto distribution, depending on whether the corresponding traffic experiences congestion or not. Finally, we show that there exist significant correlations between different ASes mostly due to relatively few highly popular prefixes.
Chapter PDF
References
Alderson, D., Chang, H., Roughan, M., Uhlig, S., Willinger, W.: The many facets of internet topology and traffic. Networks and Heterogeneous Media (2006)
Bharti, V., Kankar, P., Setia, L., Gürsun, G., Lakhina, A., Crovella, M.: Inferring invisible traffic. In: Proceedings of the 6th International Conference. ACM (2010)
Cha, M., Kwak, H., Rodriguez, P., Ahn, Y., Moon, S.: I tube, you tube, everybody tubes: analyzing the world’s largest user generated content video system. In: Proc. of the 7th ACM SIGCOMM Conference (2007)
Chang, H., Jamin, S., Mao, Z.M., Willinger, W.: An Empirical Approach to Modeling Inter-AS Traffic Matrices. In: Proceedings of the Internet Measurement Conference, IMC (2005)
Downey, A.: Evidence for long-tailed distributions in the internet. In: Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement. ACM (2001)
Erramill, V., Crovella, M., Taft, N.: An independent-connection model for traffic matrices. In: Proceedings of the 6th ACM SIGCOMM Conference on Internet Measurement (2006)
Fang, W., Peterson, L.: Inter-AS Traffic Patterns and Their Implications. In: IEEE Global Telecommunications Conference, GLOBECOM (December 1999)
Feldmann, A., Kammenhuber, N., Maennel, O., Maggs, B., De Prisco, R., Sundaram, R.: A Methodology for Estimating Interdomain Web Traffic Demand. In: Proceedings of ACM SIGCOMM Internet Measurement Conference (IMC). ACM (2004)
Gadkari, K., Massey, D., Papadopoulos, C.: Dynamics of Prefix Usage at an Edge Router. In: Spring, N., Riley, G.F. (eds.) PAM 2011. LNCS, vol. 6579, pp. 11–20. Springer, Heidelberg (2011)
Labovitz, C., Iekel-Johnson, S., McPherson, D., Oberheide, J., Jahanian, F.: Internet inter-domain traffic. In: Proceedings of the ACM SIGCOMM 2010 Conference (2010)
Nucci, A., Sridharan, A., Taft, N.: The problem of synthetically generating ip traffic matrices: initial recommendations. ACM SIGCOMM Computer Communication Review (2005)
Sen, S., Wang, J.: Analyzing peer-to-peer traffic across large networks. IEEE/ACM Transactions on Networking, ToN (2004)
Uhlig, S., Quoitin, B., Lepropre, J., Balon, S.: Providing public intradomain traffic matrices to the research community. ACM SIGCOMM Computer Communication Review (2006)
University of Oregon Route Views Project, http://www.routeviews.org
Zhang, Y., Roughan, M., Willinger, W., Qiu, L.: Spatio-temporal compressive sensing and internet traffic matrices. ACM SIGCOMM Computer Communication Review (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Mikians, J., Dhamdhere, A., Dovrolis, C., Barlet-Ros, P., Solé-Pareta, J. (2012). Towards a Statistical Characterization of the Interdomain Traffic Matrix. In: Bestak, R., Kencl, L., Li, L.E., Widmer, J., Yin, H. (eds) NETWORKING 2012. NETWORKING 2012. Lecture Notes in Computer Science, vol 7290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30054-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-30054-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30053-0
Online ISBN: 978-3-642-30054-7
eBook Packages: Computer ScienceComputer Science (R0)