Sequential Zeroing: Online Heavy-Hitter Detection on Programmable Hardware
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Ariel Orda | Isaac Keslassy | Fernando Kuipers | Belma Turkovic | Jorik Oostenbrink | A. Orda | F. Kuipers | I. Keslassy | Belma Turkovic | J. Oostenbrink
[1] Xenofontas A. Dimitropoulos,et al. Probabilistic lossy counting: an efficient algorithm for finding heavy hitters , 2008, CCRV.
[2] Roy Friedman,et al. Poster abstract: A sliding counting bloom filter , 2017, 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).
[3] Roy Friedman,et al. Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free , 2017, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications.
[4] Gaogang Xie,et al. Mnemonic Lossy Counting: An efficient and accurate heavy-hitters identification algorithm , 2010, International Performance Computing and Communications Conference.
[5] Minlan Yu,et al. Cold Filter: A Meta-Framework for Faster and More Accurate Stream Processing , 2018, SIGMOD Conference.
[6] S. Muthukrishnan,et al. Heavy-Hitter Detection Entirely in the Data Plane , 2016, SOSR.
[7] Moses Charikar,et al. Finding frequent items in data streams , 2002, Theor. Comput. Sci..
[8] David A. Maltz,et al. Network traffic characteristics of data centers in the wild , 2010, IMC '10.
[9] Roy Friedman,et al. Counting with TinyTable: Every bit counts! , 2015, 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).
[10] Peter Phaal,et al. InMon Corporation's sFlow: A Method for Monitoring Traffic in Switched and Routed Networks , 2001, RFC.
[11] Peng Liu,et al. Elastic sketch: adaptive and fast network-wide measurements , 2018, SIGCOMM.
[12] Divyakant Agrawal,et al. Efficient Computation of Frequent and Top-k Elements in Data Streams , 2005, ICDT.
[13] Ariel Orda,et al. Memento: Making Sliding Windows Efficient for Heavy Hitters , 2018, IEEE/ACM Transactions on Networking.
[14] Benoit Claise,et al. Cisco Systems NetFlow Services Export Version 9 , 2004, RFC.
[15] Roberto Bifulco,et al. A Survey on the Programmable Data Plane: Abstractions, Architectures, and Open Problems , 2018, 2018 IEEE 19th International Conference on High Performance Switching and Routing (HPSR).
[16] Liusheng Huang,et al. CountMax: A Lightweight and Cooperative Sketch Measurement for Software-Defined Networks , 2018, IEEE/ACM Transactions on Networking.
[17] George Varghese,et al. Programming Protocol-Independent Packet Processors , 2013, ArXiv.
[18] George Varghese,et al. Forwarding metamorphosis: fast programmable match-action processing in hardware for SDN , 2013, SIGCOMM.
[19] Graham Cormode,et al. An improved data stream summary: the count-min sketch and its applications , 2004, J. Algorithms.
[20] Vladimir Braverman,et al. One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon , 2016, SIGCOMM.
[21] George Varghese,et al. New directions in traffic measurement and accounting , 2002, CCRV.
[22] Ori Rottenstreich,et al. Efficient Measurement on Programmable Switches Using Probabilistic Recirculation , 2018, 2018 IEEE 26th International Conference on Network Protocols (ICNP).
[23] Roy Friedman,et al. Heavy hitters in streams and sliding windows , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.
[24] George Varghese,et al. New directions in traffic measurement and accounting , 2002, SIGCOMM '02.
[25] Fernando A. Kuipers,et al. Fast network congestion detection and avoidance using P4 , 2018, NEAT@SIGCOMM.
[26] S. Muthukrishnan,et al. Data streams: algorithms and applications , 2005, SODA '03.
[27] Steve Uhlig,et al. HeavyKeeper: An Accurate Algorithm for Finding Top- $k$ Elephant Flows , 2019, IEEE/ACM Transactions on Networking.