New directions in traffic measurement and accounting

By Cristian Estan, George Varghese. International Memory Workshop, 2001

522 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/be897a93eb627598c3eff34cd754b31c393813a6

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Citations in the corpus

Data streaming algorithms for efficient and accurate estimation of flow size distribution (2004, methodology): “For example, they have been the building blocks for detecting traffic changes [19], identifying large flows [5], and constructing Bloom filters [20] that allow both insertions and deletions (called counting Bloom filter) [21].”
One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon (2016, methodology): “Here, custom online algorithms and data structures are designed for speciﬁc metrics of interest that can yield provable resource-accuracy trade-offs (e.g., [17,18,20,31,36,38,43]).”
Planck (2014, background): “A separate related line of work looks at improving network measurements in terms of accuracy and coverage [7, 8, 9].”
Finding Hierarchical Heavy Hitters in Data Streams (2003, background): “Again there are many such algorithms [3, 13, 4, 7 ] and they dier in their performance and applicability based on the sketches they use.”
Software Defined Traffic Measurement with OpenSketch (2013, unknown): “We conservatively assume that NetFlow uses 32 Bytes per flow entry (as in [20]) and count the actual number of flow entries used by NetFlow.”
A simple algorithm for finding frequent elements in streams and bags (2003, background): “In many applications, ranging from network congestion monitoring [Estan and Varghese 2001; Pan et al. 2001] to data mining [Fang et al.”
DevoFlow: scaling flow management for high-performance networks (2011, background): “Approximate counters can be implemented using streaming algorithms [21,22,23], which are generally simple, use very little memory, and identify the ﬂows transferring the most bytes with high accuracy.”
Sketch Algorithms for Estimating Point Queries in NLP (2012, methodology): “In this section, we propose novel variants of existing sketches (see Section 2) by combining them with the conservative update process (Estan and Varghese, 2002).”
Sketch-based change detection: methods, evaluation, and applications (2003, background): “Recent research efforts have been directed towards developing scalable heavy-hitter detection techniques for accounting and anomaly detection purposes [17].”
Low-rate TCP-targeted denial of service attacks and counter strategies (2003, background): “While potentially quite harmful, the hig h-rate nature of such attacks presents a statistical anomaly to net work monitors such that the attack can potentially be detected, t h attacker identified, and the effects of the attack mitigated (s e for example, [8], [26], [34]).”