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Once seed documents are found, the remaining non-seed documents are allocated to a cluster if its seed can provide the best cover for them, or if it has the greatest seed power. C2ICM is a complex incremental clustering algorithm, but it is useful for updating clusters of very large and dynamic data sets. As many computational algorithms and software must be able to scale up to meet continuous challenges from increasingly large data sets, notably the web, methods such as the incremental clustering will be an increasingly useful and generic tool.
CAIDA’s short-term plans include developing 3D visualizations of Skitter measurements, using additional active and passive measurement hosts throughout the Internet, and analyzing trends in these trafﬁc data. Similar work has been done at Matrix Information Directory Services (MIDS) in mapping the Internet. MIDS produces an animated map known as the Internet Weather Report7 (IWR), which updates network latencies on the Internet six times a day, probed from MIDS’s headquarters in Texas to over 4000 domains around the world.
Visualization of macro-level trafﬁc patterns can give insights into several areas; for example, mapping dynamic changes in Internet topology, tracking abnormal delays, and identifying bottleneck routers and critical paths in the Internet infrastructure. Interestingly, CAIDA is planning to tap the Skitter output data with a geographical database of various crucial backbone networks on the Internet, the MBone and caching hierarchy topology. These data together can help engineers to pinpoint routing anomalies, and track round-trip times and packet loss.