Now suppose that six other packets, launched at the same time, travel from Station A to Station C with a similar pattern of transit times. Now suppose that a third set of packets travels from Station A to Station D but shows a very different pattern. From these data, the Felix team infers that packets traveling from A to B pass through the same sources of delay as those traveling from A to C. Thus, the route for AB and AC must share common elements. To discover the shape of the network, the Felix team analyzes the correlations among the time series of many pairs of monitoring stations. Huitema compares this approach to a CT scan.
Rich measurements demand robust, scalable analytic techniques.
With many stations and many routes for each station pair, the task rapidly grows complex. The project has other applications, too. For example, it could help identify optimal routes. It could assist network engineering efforts by identifying sources of congestion. It could help the provider of a distributed service decide which server should serve certain information to a given client.