Towards a meaningful MRA of traffic matrices
Date
2008
Authors
Rincon, D.
Roughan, M.
Willinger, W.
Editors
Papagiannaki, K.
Zhang, Z.-L.
Zhang, Z.-L.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement, 20 October, 2008:pp.331-336
Statement of Responsibility
David Rincon; Matthew Roughan and Walter Willinger
Conference Name
Internet Measurement Conference (2008 : Vouliagmeni, Greece)
Abstract
Most research on traffic matrices (TM) has focused on finding models that help with inference, but not with other important tasks such as synthesis of TMs, traffic prediction, or anomaly detection. In this paper we approach the problem of a general model for traffic matrices, and argue that such a model must be sparse, i.e., have a small number of parameters in comparison to the size of the TM. A Multi-Resolution Analysis (MRA) of TMs can provide such a sparse representation. The Diffusion Wavelet (DW) transform is a good choice as a MRA tool here, because it inherently adapts to the structure of the underlying network. The paper describes our construction of the two-dimensional version of the DW transform and shows how to use it for our proposed MRA of TMs. The results obtained with operational networks confirm the sparseness of the DW-based TM analysis approach and its applicability to other TM-related tasks.
School/Discipline
Dissertation Note
Provenance
Description
Copyright © 2008 ACM