1. 1 Network Tomography Don Towsley UMass-Amherst

2. 2 Network Tomography - I Goal: obtain detailed picture of a network/internet from end-to-end views  infer topology /connectivity

3. 3 Network Tomography - I Goal: obtain detailed picture of a network/internet from end-to-end views  infer link-level  loss  delay  available bandwidth...

4. 4 Network Tomography - II Goal: obtain detailed picture of external behavior from internal views  infer source- destination traffic matrix from internal traffic counts w 015 x 221 y 345 z … w x y z 1 2 3 1 2 … 1 2 3 - 341 123 - … … ?

5. 5 Brain Tomography unknown object counting & projection Maximum likelihood estimate perform inference inverse function problem data statistical model brain model

6. 6 Network Tomography routing & counting data queuing behavior binomial perform inference inverse function problem

7. 7 Talks  C. Dovrolis (discussant, J. Crowcroft)  inference of path characteristics  F. Lopresti (discussant, C. Diot)  inference of network characteristics  K. Salamatian (discussant, J. Kurose)  interpreting measurements