Distributed data centric similarity storage scheme in wireless sensor network

Due to the sensor hardware inaccuracy and deviation of environmental parameter, detection of imprecise data by sensor is very likely. Hence, similarity searching problem is receiving significant consideration and became an important problem to resolve. However, most of the state-of-the-art Data Centric Storage (DCS) Schemes lack optimization for similarity query of the events. This paper proposes a distributed metric based data centric similarity storage scheme (DMDCS). DMDCS takes the advantage of the idea of a vector index method, called iDistance and transforms the issue of similarity searching into the problem of interval search in one dimension. Experimental results show that DMDCS yields significant improvements on the efficiency of data querying compared with existing approaches.