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Efficient algorithms and techniques to detect and identify large flows in ahigh throughput traffic stream in the SDN match-and-action model are presented.This is in contrast to previous work that either deviated from the match andaction model by requiring additional switch level capabilities or did notexploit the SDN data plane. Our construction has two parts; (a) how to samplein an SDN match and action model, (b) how to detect large flows efficiently andin a scalable way, in the SDN model.  Our large flow detection methods provide high accuracy and present a good andpractical tradeoff between switch - controller traffic, and the number ofentries required in the switch flow table. Based on different parameters, wedifferentiate between heavy flows, elephant flows and bulky flows and presentefficient algorithms to detect flows of the different types.  Additionally, as part of our heavy flow detection scheme, we present samplingmethods to sample packets with arbitrary probability $p$ per packet or per bytethat traverses an SDN switch.  Finally, we show how our algorithms can be adapted to a distributedmonitoring SDN setting with multiple switches, and easily scale with the numberof monitoring switches.

Detecting Heavy Flows in the SDN Match and Action Model