Scalable Bloom Filters
نویسندگان
چکیده
Bloom Filters provide space-efficient storage of sets at the cost of a probability of false positives on membership queries. The size of the filter must be defined a priori based on the number of elements to store and the desired false positive probability, being impossible to store extra elements without increasing the false positive probability. This leads typically to a conservative assumption regarding maximum set size, possibly by orders of magnitude, and a consequent space waste. This paper proposes Scalable Bloom Filters, a variant of Bloom Filters that can adapt dynamically to the number of elements stored, while assuring a maximum false positive probability.
منابع مشابه
Dynamic Bloom Filters: Analysis and usability
Bloom Filters (BF) [1] are space-e cient datastructures that allow membership queries from a set. In most recent years they have gained great momentum and various tweaks to them have been proposed to achieve speci c goals. Dynamic Bloom Filters (DBF) have been proposed [2] as a method to implement Bloom Filters in a scalable environment, i.e. where the nal size of a dataset is not known in adva...
متن کاملP-LUPOSDATE: Using Precomputed Bloom Filters to Speed Up SPARQL Processing in the Cloud
Increasingly data on the Web is stored in the form of Semantic Web data. Because of today’s information overload, it becomes very important to store and query these big datasets in a scalable way and hence in a distributed fashion. Cloud Computing offers such a distributed environment with dynamic reallocation of computing and storing resources based on needs. In this work we introduce a scalab...
متن کاملBloofi: Multidimensional Bloom Filters
Bloom filters are probabilistic data structures commonly used for approximate membership problems in many areas of Computer Science (networking, distributed systems, databases, etc.). With the increase in data size and distribution of data, problems arise where a large number of Bloom filters are available, and all them need to be searched for potential matches. As an example, in a federated cl...
متن کاملBloom Filters in Probabilistic Verification
Probabilistic techniques for verification of finite-state transition systems offer huge memory savings over deterministic techniques. The two leading probabilistic schemes are hash compaction and the bitstate method, which stores states in a Bloom filter. Bloom filters have been criticized for being slow, inaccurate, and memory-inefficient, but in this paper, we show how to obtain Bloom filters...
متن کاملAn Iterative Two-Party Protocol for Scalable Privacy-Preserving Record Linkage
Record linkage is the process of identifying which records in different databases refer to the same realworld entities. When personal details of individuals, such as names and addresses, are used to link databases across different organisations, then privacy becomes a major concern. Often it is not permissible to exchange identifying data among organisations. Linking databases in situations whe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Inf. Process. Lett.
دوره 101 شماره
صفحات -
تاریخ انتشار 2007