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Flow based traffic measurement today is a very important tool for network management, but suffers from huge amounts of data and a lack of scalability. Therefore it is important to find methods to reduce that amount of data for applications like long-term archiving or filtering in mediators to improve scalability. A fact that helps here is, that general internet traffic has power-law characteristics and that for many applications it is enough to only look at the large flows. In this paper, the authors introduce Mouse Trapping, a flow data reduction method that keeps the large flow records, while the small flow records are aggregated or even removed.
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