A Sparse Dirty Data Process Method Based on Alternative Projection for Traffic Matrix Estimation

Estimation of traffic matrices, which provides critical input for network capacity planning and traffic engineering, will be contaminated by the dirty data created by troubles such us hardware/software/transmission. To solve this problem, a SNMP-data-self based sparse dirty data model and a sparse dirty data Processing Algorithm based on alternating projection are proposed here. The former occupies merit of no checkout between measurement of OD flows and SNMP data, the latter obtains norm minimized solution through alternating projection method. Comparing to other main algorithms, this method has lower measuring overhead and computing complexity. Moreover, the simulation experiment shows high accuracy.

[1]  Mikael Johansson,et al.  Traffic matrix estimation on a large IP backbone: a comparison on real data , 2004, IMC '04.

[2]  Albert G. Greenberg,et al.  Network anomography , 2005, IMC '05.

[3]  Qi Zhao,et al.  Robust traffic matrix estimation with imperfect information: making use of multiple data sources , 2006, SIGMETRICS '06/Performance '06.

[4]  Konstantina Papagiannaki,et al.  A distributed approach to measure IP traffic matrices , 2004, IMC '04.

[5]  Y. Vardi,et al.  Network Tomography: Estimating Source-Destination Traffic Intensities from Link Data , 1996 .

[6]  D. Donoho.  For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution , 2006 .

[7]  Javier Portilla,et al.  L0-Norm-Based Sparse Representation Through Alternate Projections , 2006, 2006 International Conference on Image Processing.

[8]  Christophe Diot,et al.  Traffic matrix estimation: existing techniques and new directions , 2002, SIGCOMM 2002.

[9]  Konstantina Papagiannaki,et al.  Traffic matrices: balancing measurements, inference and modeling , 2005, SIGMETRICS '05.

[10]  Attahiru Sule Alfa,et al.  IP Traffic Matrix Estimation Methods: Comparisons and Improvements , 2006, 2006 IEEE International Conference on Communications.

[11]  Albert G. Greenberg,et al.  Fast accurate computation of large-scale IP traffic matrices from link loads , 2003, SIGMETRICS '03.

[12]  BERNARD M. WAXMAN,et al.  Routing of multipoint connections , 1988, IEEE J. Sel. Areas Commun..

[13]  Dante C. Youla,et al.  Generalized Image Restoration by the Method of Alternating Orthogonal Projections , 1978 .

[14]  Carsten Lund,et al.  An information-theoretic approach to traffic matrix estimation , 2003, SIGCOMM '03.

[15]  Zhu Shi-rui.  Research on Traffic Matrix Estimation Based on Gauss Mixed Model , 2009 .

[16]  Abhishek Kumar,et al.  Data streaming algorithms for accurate and efficient measurement of traffic and flow matrices , 2005, SIGMETRICS '05.

[17]  Carsten Lund,et al.  Estimating point-to-point and point-to-multipoint traffic matrices: an information-theoretic approach , 2005, IEEE/ACM Transactions on Networking.