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Probabilistic lossy counting: an efficient algorithm for finding heavy hitters

8 years 8 months ago
Probabilistic lossy counting: an efficient algorithm for finding heavy hitters
Knowledge of the largest traffic flows in a network is important for many network management applications. The problem of finding these flows is known as the heavy-hitter problem and has been the subject of many studies in the past years. One of the most efficient and well-known algorithms for finding heavy hitters is lossy counting [29]. In this work we introduce probabilistic lossy counting (PLC), which enhances lossy counting in computing network traffic heavy hitters. PLC uses on a tighter error bound on the estimated sizes of traffic flows and provides probabilistic rather than deterministic guarantees on its accuracy. The probabilistic-based error bound substantially improves the memory consumption of the algorithm. In addition, PLC reduces the rate of false positives of lossy counting and achieves a low estimation error, although slightly higher than that of lossy counting. We compare PLC with state-of-the-art algorithms for finding heavy hitters. Our experiments using real tra...
Xenofontas A. Dimitropoulos, Paul Hurley, Andreas
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where CCR
Authors Xenofontas A. Dimitropoulos, Paul Hurley, Andreas Kind
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