Theory and Network Applications of Dynamic Bloom Filters

Abstract— A bloom filter is a simple, space-efficient, randomized data structure for concisely representing a static data set, in order to support approximate membership queries. It has great potential for distributed applications where systems need to share information about what resources they have. The space efficiency is achieved at the cost of a small probability of false positive in membership queries. However, for many applications the space savings and short locating time consistently outweigh this drawback. In this paper, we introduce dynamic bloom filters (DBF) to support concise representation and approximate membership queries of dynamic sets, and study the false positive probability and union algebra operations. We prove that DBF can control the false positive probability at a low level by adjusting the number of standard bloom filters used according to the actual size of current dynamic set. The space complexity is also acceptable if the actual size of dynamic set ...

• Type: Conference
• Year: 2006
• Where: INFOCOM
• Authors: Deke Guo, Jie Wu, Honghui Chen, Xueshan Luo
• Keywords: Approximate Membership Queries, Bloom filters, Communications, False Positive Probability, INFOCOM 2006