Abstract
The Wireless Sensor Network similarity search problem has received considerable research attention due to sensor hardware imprecision and environmental parameter variations. Most of the state-of-the-art distributed data centric storage (DCS) schemes lack optimization for similarity queries of events. In this paper, a DCS scheme with metric based similarity searching (DCSMSS) is proposed. DCSMSS takes motivation from vector distance index, called iDistance, in order to transform the issue of similarity searching into the problem of an interval search in one dimension. In addition, a sector based distance routing algorithm is used to efficiently route messages. Extensive simulation results reveal that DCSMSS is highly efficient and significantly outperforms previous approaches in processing similarity search queries.
Highlights
This paper considers a distributed information delivery and search service for one or more applications in a Wireless Sensor Network (WSN) that utilizes in-network storage, which is known as
In a multi-hop fashion to the corresponding sector for storage. In this inter-sector communication, Sector Head (SH) continue forwarding their packets to their immediate neighbor SH, which lies on the same row in the virtual grid (Figure 1a) until the packet reaches the SH that is on the same column as the destination sector
DCS scheme with metric based similarity searching (DCSMSS) was applied to a range of WSN scenarios utilizing modeling, simulation and a statistical analysis and found to provide lower latency and improved search accuracy when compared to relatively recent alternate approaches
Summary
This paper considers a distributed information delivery and search service for one or more applications in a Wireless Sensor Network (WSN) that utilizes in-network storage, which is known as. Storage with Metric based Similarity Searching (DCSMSS), which is a highly scalable distributed information service based on Disk Based Data Centric Storage (DBDCS) [2] that incorporates similarity searching. In this paper distances between data points and reference points in the multi-dimensional space have been mapped to one-dimensional values. The DCSMSS scheme presented is used to balance information transfer loads across the network, enhance reliability and provide efficient similarity searching within a distributed network for two types of queries—range query and k-query. The domain of the derived hash key of an aggregated sensed event, denoted by HD, is mapped into the metric space of the DBDCS architecture. In order to store an event, the target sector is mapped based on the derived hash key and pivot points.
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