Abstract
Efficient object searching mechanisms are essential in large-scale networks. Many studies have been done on distributed hash tables (DHTs), which are a kind of peer-to-peer system. In DHT networks, we can certainly get the desired objects if they exist. However, multi-word searches generate much communication traffic. Many studies have tried to reduce this traffic by using bloom filters, which are space-efficient probabilistic data structures. In using such filters, all nodes in a DHT must share their false positive rate parameter. However, the best false positive rate differs from one node to another. In this paper, we provide a method of determining the best false positive rate, and we use a new filter called a flexible bloom filter, to which each node can set the approximately best false positive rate. Experiments showed that the flexible bloom filter was able to greatly reduce the traffic.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.