| Paper: | SPTM-L2.5 | ||
| Session: | Networks and Communication Systems Modeling | ||
| Time: | Tuesday, May 18, 16:50 - 17:10 | ||
| Presentation: | Lecture | ||
| Topic: | Signal Processing Theory and Methods: Detection, Estimation, and Class. Thry & Apps. | ||
| Title: | NETWORK TOPOLOGY DISCOVERY USING FINITE MIXTURE MODELS | ||
| Authors: | Meng-Fu Shih; University of Michigan | ||
| Alfred O. Hero III; University of Michigan | |||
| Abstract: | In this article we propose a network topology estimation strategy using unicast end-to-end packet pair delay measurements that is based on mixture models for the delay covariances. An unsupervised learning algorithms is applied to estimate the number of mixture components and delay covariances. The leaf pairs are clustered by a MAP criterion and are passed to a hierarchical topology construction algorithm to rebuild the tree specifying. Results from a ns simulation show that our algorithm can identify a network tree with 8 leaf nodes. | ||
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