Analyzing the Optimal Use of Bloom Filters in Wireless Sensor Networks Storing Replicas

We study the problem of optimal parameter selection for Bloom filters in content-based routing. In constrained environments, such as sensor network, optimizing lengths of the filters used and the number of hash functions employed can lead to significant reduction of memory overhead and false positives. We demonstrate by analytical calculations and extensive simulations that the commonly used heuristics for choosing these parameters are suboptimal especially in networks storing replicas of the data for redundancy. We show specifically how network topology and use of replication can be taken into account when selecting the parameter values used. Our results show that memory consumption can be reduced by up to 50% compared to usual approaches, and that the occurrence of false positives can be significantly reduced as well.