| Paper: | SPTM-L2.6 | ||
| Session: | Networks and Communication Systems Modeling | ||
| Time: | Tuesday, May 18, 17:10 - 17:30 | ||
| Presentation: | Lecture | ||
| Topic: | Signal Processing Theory and Methods: System Modeling, Representation, & Identification | ||
| Title: | NETWORK TOMOGRAPHY BASED ON FLOW LEVEL MEASUREMENTS | ||
| Authors: | Dogu Arifler; University of Texas, Austin | ||
| Gustavo de Veciana; University of Texas, Austin | |||
| Brian Evans; University of Texas, Austin | |||
| Abstract: | Internet traffic primarily consists of packets from elastic flows, i.e. Web transfers, file transfers (FTP), and e-mail, whose transfers are mediated via the Transmission Control Protocol. We develop a conditional sampling technique to analyze throughput correlations among elastic flow classes based on flow level measurements from current network traffic monitoring tools. The primary contributions of this paper are: (1) a demonstration of throughput correlation among temporally overlapping flows on congested resources by using analytical/simulation models, and (2) application of a multivariate statistical method (principal components) to infer network properties, such as the number of shared resources by flows in the network from non-intrusive, flow level measurements collected at a single site. Our proposal for using flow level measurements to infer network properties differs significantly from previous network tomography research that has employed end-to-end packet level measurements for making inferences. | ||
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