Fingerprinting network problems (2010-2011)

During my internship at Microsoft Research India, I contributed to the development of a tool - Deja vu - for identifying and classifying network problems. The principle is to generate simple, human-readable signatures by extracting a series of features from network traces. Deja Vu then uses a novel learning algorithm to categorize problem signatures in clusters. The advantage of such approach is that signatures can be effectively used to map failures to known problems (existing clusters), and to detect the occurrence of new problems (new clusters). Also, the signatures - being simple and human readable -can be used by experts to diagnose problems instead of time-consuming network capture analysis. Details of Deja Vu were discussed in our CoNEXT 2011 paper.