Bloom filters are a probabilistic data structure used to evaluate set membership. A group of hash functions are used to map elements into a Bloom filter and to test elements for membership. In this paper, we propose using multiple groups of hash functions and selecting the group that generates the Bloom filter instance with the smallest number of bits set to 1. We evaluate the performance of this new Best-of-N method using order statistics and an actual implementation. Our analysis shows that significant reduction in the probability of a false positive can be achieved. We also propose and evaluate a new method that uses a Random Number Generator (RNG) to generate multiple hashes from one initial “seed ” hash. This RNG method (motivated by a method from Kirsch and Mitzenmacher) makes the computational expense of the Best-of-N method very modest. The target application is a power management proxy for P2P applications executing in a resource-constrained “SmartNIC”
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