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SSG Seminar Abstract


Tracking Transaction Using Timestamps

Anima Anandkumar
SSG, MIT


The issue of tracking using timestamps arises in many enterprise systems which lack proper monitoring instrumentation and only have log-records with timestamps.

We consider tracking transactions in a queuing network using timestamps generated at the network nodes. In general, the optimal maximum likelihood tracking has exponential complexity in the number of transactions. However, we prove that maximum likelihood tracking reduces to a series of bipartite minimum weight perfect matchings for the case of acyclic infinite-server queuing networks. Hence, maximum likelihood tracking is equivalent to decentralized matching of timestamps in small clusters of network nodes. Further, we show that the tracking system has least accuracy under exponential or uniform services for a given set of timestamps.



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