TY - GEN
T1 - Counting with tinytable
T2 - 17th International Conference on Distributed Computing and Networking, ICDCN 2016
AU - Einziger, Gil
AU - Friedman, Roy
N1 - Publisher Copyright:
© 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2016/1/4
Y1 - 2016/1/4
N2 - Counting Bloom filters (CBF) and their variants are data structures that support membership or multiplicity queries with a low probabilistic error. Yet, they incur a significant memory space overhead when compared to lower bounds as well as to (plain) Bloom filters, which can only represent set membership without removals. This work presents TinyTable, an efficient hash table based algorithm that supports membership queries, removals and multiplicity queries (statistics). TinyTable improves space efficiency by as much as 28% compared to CBF variants and as much as 60% for monitoring flow statistics. When the required false positive rate is smaller than 1%, TinyTable is even slightly more space efficient than (plain) Bloom filters. Our performance study shows that TinyTable has acceptable runtime overheads.
AB - Counting Bloom filters (CBF) and their variants are data structures that support membership or multiplicity queries with a low probabilistic error. Yet, they incur a significant memory space overhead when compared to lower bounds as well as to (plain) Bloom filters, which can only represent set membership without removals. This work presents TinyTable, an efficient hash table based algorithm that supports membership queries, removals and multiplicity queries (statistics). TinyTable improves space efficiency by as much as 28% compared to CBF variants and as much as 60% for monitoring flow statistics. When the required false positive rate is smaller than 1%, TinyTable is even slightly more space efficient than (plain) Bloom filters. Our performance study shows that TinyTable has acceptable runtime overheads.
KW - Approximate counting
KW - Counting Bloom filter
KW - Hash tables
UR - http://www.scopus.com/inward/record.url?scp=84961180043&partnerID=8YFLogxK
U2 - 10.1145/2833312.2833449
DO - 10.1145/2833312.2833449
M3 - Conference contribution
AN - SCOPUS:84961180043
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 17th International Conference on Distributed Computing and Networking, ICDCN 2016
PB - Association for Computing Machinery
Y2 - 4 January 2016 through 7 January 2016
ER -