Sensor Data & Analysis Framework (SDAF) Data Warehouse
October 2007
Eddy Cheung, The MITRE Corporation
Stephan Nadeau, The MITRE Corporation
Don Landing, The MITRE Corporation
Mark Munson, The MITRE Corporation
Jennifer Casper, The MITRE Corporation
ABSTRACT
The Sensor Data & Analysis Framework (SDAF) Data Warehouse is part of the SDAF
project. As more and more sensors are producing volumes of data regarding objects that
change with respect to location and time, evaluating this stream of information in a timely
fashion requires the integration of current and historical data. The SDAF research project
seeks to investigate and understand various approaches to integrating streamed and historical
sensor data to support spatio-temporal queries. The SDAF Data Warehouse (SDAF DW)
effort experiments with different techniques to store and organize the historical sensor data
efficiently in a persistent data store.
In this paper, we will discuss the finding that to support spatial queries of objects relating to
location and time, it is best to partition the data by date/time. There are two advantages to the
approach. First, partition elimination keeps the number of partitions to search for a query to a
minimum. Second, as the size of the database grows, the number of partitions to search for the
same query remains the same, thereby keeping the response time relatively constant.
Additional Search Keywords
SDAF, Sensor Data and Analysis Framework, Moving Target indicator, MTI,
SMTI, GMTI, Data Warehouse
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