Performance Evaluation of Bloom Multifilters

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http://urn.fi/URN:NBN:fi:hulib-201804131683
Titel: Performance Evaluation of Bloom Multifilters
Författare: Concas, Francesco
Medarbetare: Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta, Tietojenkäsittelytieteen laitos
University of Helsinki, Faculty of Science, Department of Computer Science
Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap
Utgivare: Helsingin yliopisto
Datum: 2018
Språk: eng
Permanenta länken (URI): http://urn.fi/URN:NBN:fi:hulib-201804131683
http://hdl.handle.net/10138/234248
Nivå: pro gradu-avhandlingar
Ämne: Computer science
Tietojenkäsittelytiede
Datavetenskap
Abstrakt: The Bloom Filter is a space-efficient probabilistic data structure that deals with the problem of set membership. The space reduction comes at the expense of introducing a false positive rate that many applications can tolerate since they require approximate answers. In this thesis, we extend the Bloom Filter to deal with the problem of matching multiple labels to a set, introducing two new data structures: the Bloom Vector and the Bloom Matrix. We also introduce a more efficient variation for each of them, namely the Optimised Bloom Vector and the Sparse Bloom Matrix. We implement them and show experimental results from testing with artificial datasets and a real dataset.


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