Abstract
Bloom filter is a bit array (a one-dimensional storage structure) that provides a compact representation for a set of data, which can be used to answer the membership query in an efficient manner with possible false positives. It has a lot of applications in many areas. In this paper, we further improve Bloom filter by proposing the use of multi-dimensional matrix to replace the one-dimensional structure. Based on our N-dimensional matrix structure, we propose four kinds of filter implementation, namely OFFF, ZFFF, WOFF, FFF (we refer it as Feng Filter). We prove that the false positive rate of our method is lower than the traditional one-dimensional Bloom filter. We also present the detailed implementation of our proposed filter. The traditional Bloom filter can be regarded as a special case of the Feng Filter.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
