An Improved Construction for Counting Bloom Filters
By Flavio Bonomi, Michael M. Mitzenmacher, Rina Panigrahy, Sushil Singh, George Varghese. Embedded Systems and Applications, 2006
399 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Materials Chemistry
View Paper: https://www.semanticscholar.org/paper/13bf79b773cc84590d3efeb88187f2675dea4b81
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- D. Andersen
- Michael Kaminsky
- Bin Fan
- Christian Esteve Rothenberg
- Sasu Tarkoma
- E. Lagerspetz
- Dean M. Tullsen
- Nuwan Jayasena
In Materials Chemistry
- Christian Esteve Rothenberg
- Michael Kaminsky
- Bin Fan
- D. Andersen
- Sasu Tarkoma
- E. Lagerspetz
- Michael M. Mitzenmacher
Citations in the corpus
- Horton Tables: Fast Hash Tables for In-Memory Data-Intensive Computing (2016, methodology): “To this end, this paper presents Horton tables,2 a carefully retrofitted bucketized cuckoo hash table, which trades a small amount of space for achieving positive and negative lookups that touch close to 1 bucket apiece.”
- Theory and Practice of Bloom Filters for Distributed Systems (2012, methodology): “[20] presented a data structure based on -”
- Invertible bloom lookup tables (2011, neutral): “, see [7, 8, 33] for some excellent surveys).”
- SketchVisor: Robust Network Measurement for Software Packet Processing (2017, methodology): “The fast path is volume-based and tracks byte counts, yet we can also use it to track connectivity-based statistics (e.g., DDoS, superspreader, and cardinality) by converting connectivity-based sketches in the normal path into volume-based sketches, similar to the approach in Counting Bloom Filter [”
- Cuckoo Filter: Practically Better Than Bloom (2014, methodology): “To address this issue, d-left counting Bloom filters use an additional counter in each table entry and additional indirections [5].”