Dynamic count filters
Larriba-Pey, J. L.
Google Scholar check
MetadataShow full item record
Bloom filters are not able to handle deletes and inserts on multisets over time. This is important in many situations when streamed data evolve rapidly and change patterns frequently. Counting Bloom Filters (CBF) have been proposed to overcome this limitation and allow for the dynamic evolution of Bloom filters. The only dynamic approach to a compact and efficient representation of CBF are the Spectral Bloom Filters (SBF). In this paper we propose the Dynamic Count Filters (DCF) as a new dynamic and space-time efficient representation of CBF. Although DCF does not make a compact use of memory, it shows to be faster and more space efficient than any previous proposal. Results show that the proposed data structure is more efficient independently of the incoming data characteristics.
Showing items related by title, author, creator and subject.
Cusick, T. A.; Iezekiel, Stavros; Miles, R. E. (1997)
Cusick, T. A.; Iezekiel, Stavros; Miles, R. E.; Sales, S.; Capmany, J. (1997)
Loizou, Christos P.; Kasparis, Takis; Christodoulides, Paul; Theofanous, Charoula; Pantzaris, Marios C.; Kyriacou, Efthyvoulos C.; Pattichis, Constantinos S. (2012)Noise reduction is essential for increasing the visual quality or as a preprocessing step for further automated analysis in video sequences and video coding. The objective of this work was to investigate four different ...