Abstract — Many network solutions and overlay networks uti-lize probabilistic techniques to reduce information processing and networking costs. This survey article presents a number of frequently used and useful probabilistic techniques. Bloom filters and their variants are of prime importance, and they are heavily used in various distributed systems. This has been reflected in recent research and many new algorithms have been proposed for distributed systems that are either directly or indirectly based on Bloom filters. In this survey, we give an overview of the basic and advanced techniques, reviewing over 20 variants and discussing their application in distributed systems, in particular for caching, peer-to-peer systems, routing and forw...
Bloom filter based algorithms have proven successful as very efficient technique to reduce communica...
Bloom filters are efficient randomized data structures for membership queries on a set with a certai...
Bloom filters are probabilistic data structures commonly used for approximate membership problems in...
Many network solutions and overlay networks utilize probabilistic techniques to reduce information p...
Bloom filter is a probabilistic data structure to filter a membership of a set. Bloom filter returns...
Where distributed agents must share voluminous set membership information, Bloom filters provide a c...
Where distributed agents must share voluminous set membership information, Bloom filters provide a c...
Abstract: This paper surveys the mathematics behind Bloom filters, some important variations and ne...
International audienceWhere distributed agents must share voluminous set membership information, Blo...
Bloom filters make use of a “probabilistic ” hash-coding method to reduce the amount of space requir...
Bloom filtrelerini ve çeşitlerini inceleyen bir çalışmanın özetidir. Bloom filtresi sorgulama üyelik...
Bloom filter is a widely-used data structure that concisely represents a large set of contents for a...
Internet was designed to provide source to destination communication and it had shown good resilienc...
The Bloom Filter (BF), a space-and-time-efficient hashcoding method, is used as one of the fundament...
Bloom filters impress by their sheer elegance and have become a widely and indiscriminately used too...
Bloom filter based algorithms have proven successful as very efficient technique to reduce communica...
Bloom filters are efficient randomized data structures for membership queries on a set with a certai...
Bloom filters are probabilistic data structures commonly used for approximate membership problems in...
Many network solutions and overlay networks utilize probabilistic techniques to reduce information p...
Bloom filter is a probabilistic data structure to filter a membership of a set. Bloom filter returns...
Where distributed agents must share voluminous set membership information, Bloom filters provide a c...
Where distributed agents must share voluminous set membership information, Bloom filters provide a c...
Abstract: This paper surveys the mathematics behind Bloom filters, some important variations and ne...
International audienceWhere distributed agents must share voluminous set membership information, Blo...
Bloom filters make use of a “probabilistic ” hash-coding method to reduce the amount of space requir...
Bloom filtrelerini ve çeşitlerini inceleyen bir çalışmanın özetidir. Bloom filtresi sorgulama üyelik...
Bloom filter is a widely-used data structure that concisely represents a large set of contents for a...
Internet was designed to provide source to destination communication and it had shown good resilienc...
The Bloom Filter (BF), a space-and-time-efficient hashcoding method, is used as one of the fundament...
Bloom filters impress by their sheer elegance and have become a widely and indiscriminately used too...
Bloom filter based algorithms have proven successful as very efficient technique to reduce communica...
Bloom filters are efficient randomized data structures for membership queries on a set with a certai...
Bloom filters are probabilistic data structures commonly used for approximate membership problems in...