Updating aggregation tree in distributed spatial telemetric data warehouse

In this paper we present a spatial telemetric data warehouse (STDW) system that we use for aggregation and analysis of huge amounts of spatial data. The data is generated by utilities meters communicating via radio. In order to provide a sufficient efficiency of our system we propose data and workload distribution as well as advanced indexing techniques. As a data model we applied a cascaded star model that is a spatial development of a standard star schema. We use a dynamic indexing structure called aggregation tree. The index operation is tightly integrated with the spatial character of the data. In this paper we address a few interesting details concerning the aggregation tree: indexing structure materialization, memory managing algorithm and tree updating. The system is written in Java; as the database we use Oracle 9i. Basing on the tests results, we prove that the distributed system significantly surpasses the centralized version in terms of efficiency. We also show that a selective materialization of indexing structure fragments strongly increases system efficiency.