Traffic matrix tracking using kalman filters

Performance Evaluation Review

Volumn 33, Issue 3, 2005, Pages 24-31

  Soule, Augustin ^a   Salamatian, Kavé ^a   Nucci, Antonio ^b   Taft, Nina ^c  

^a UNIVERSITÉ PIERRE ET MARIE CURIE   (France)

^b Narus Inc   (United States)

^c INTEL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER NETWORKS; KALMAN FILTERING; LINEAR SYSTEMS; MATHEMATICAL MODELS; MATRIX ALGEBRA; STATE SPACE METHODS;

STATE SPACE MODEL; TRAFFIC MATRIX ESTIMATION; TRAFFIC MATRIX TRACKING;

TELECOMMUNICATION TRAFFIC;

EID: 33646420611     PISSN: 01635999     EISSN: 01635999     Source Type: Conference Proceeding    
DOI: 10.1145/1111572.1111580     Document Type: Conference Paper

References (9)

1. CISCO. Netflow services and applications, 2002.
2. T. Kailath, A. H. Sayed, B. Hassibi, A. H. Sayed, and B. Hassibi. Linear Estimation. Prentice Hall, 2000.
3. A. Lakhina, M. Crovella, and C. Diot. Diagnosing network-wide traffic anomalies. In Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications. ACM Press, 2004.
4. A. Medina, N. Taft, K. Salamatian, S. Bhattacharyya, and C. Diot. Traffic matrix estimation: existing techniques and new directions. In Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications, pages 161-174. ACM Press, 2002.
5. K. Papagiannaki, N. Taft, and A. Lakhina. A Distributed Approach to Measure IP Traffic Matrices. In ACM Sigcomm Internet Measurement Conference, Taormina, ITALY, Oct. 2004.
6. R. Shumway and D. Stoffer. Dynamic linear models with switching. Journal of the the American Statistical Association, 86, 1991.
7. A. Soule, A. Lakhina, N. Taft, K. Papagiannaki, K. Salamatian, A. Nucci, M. Crovella, and C. Diot. Traffic matrices: Balancing measurments, inference and modeling. In ACM Sigmetrics, Banff, June 2005.
8. A. Soule, A. Nucci, R. Cruz, and E. L. and Nina Taft. How to identify and estimate the largest traffic matrix elements in a dynamic environment. In ACM Sigmetrics, New York, June 2004.
9. Y. Zhang, M. Roughan, C. Lund, and D. Donoho. An information-theoretic approach to traffic matrix estimation. In Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications, pages 301-312. ACM Press, 2003.