Selection Optimization of Bloom Filter-Based Index Services in Ubiquitous Embedded Systems

In pervasive systems, data object is stored in distributed storage nodes. High performance indexing service plays an import rule in the efficient utilization of the data in ubiquitous computing. The embedded systems on the ubiquitous nodes, however, have constraint memory space and energy supply. How to design efficient index service with limited resource requirement on the embedded systems is a key technique in pervasive computing. In this paper, we compare two types of Bloom filter-based index services: Lightweight Bloom filter Array and Two-tier Bloom filter Array. The lookup time and the energy consumption are taken into consideration when measuring the performance of the two index services. We analyse the characteristics of the two algorithms with the analytical expressions. Further, experiments under the same conditions are performed and the results are analyzed. Finally, this paper gives the optimization suggestion for selecting one out of the two algorithms under different usage circumstances.