Supporting spatial aggregation in sensor network databases

Sensor networks are unattended deeply distributed systems whose schema can be conceptualized using the relational model. Aggregation queries on the data sampled at each ode are the main means to extract the abstract characteristics of the surrounding environment. However, the non-uniform distribution of the sensor nodes in the environment leads to inaccurate results generated by the aggregation queries. In this paper, we introduce "spatial aggregations" that take into consideration the distribution of the values generated by the sensor nodes. We propose the use of spatial interpolation methods derived from the fields of spatial statistics and computational geometry to answer spatial aggregations. In particular, we study Spatial Moving Average (SMA), Voronoi Diagram and Triangulated Irregular Network (TIN). Investigating these methods for answering spatial average queries, we show that the average value on the data samples weighted by the area of the Voronoi cell of the corre...

• Type: Conference
• Year: 2004
• Where: GIS
• Authors: Mehdi Sharifzadeh, Cyrus Shahabi
• Keywords: Database, GIS 2004, Spatial Aggregations, Spatial Average Queries, Spatial Interpolation Methods