Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
A Kalman filter updating method for the indoor moving object database
Expert Systems with Applications: An International Journal
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One of the challenges to build a high performance Moving Object Database (MOD) is how to efficiently process the location stream which are inserted at a high rate beyond the tolerance of database, while location accuracy needs to be preserved. Based on CAMEL, an MOD prototype implemented in IBM China Research Lab, we present the location filter module and integrate it into the CAMEL to address the issue. The proposed location filter includes two components: the on-line location filter to filter the location stream online by filtering algorithm plug-ins, and the temporal location manager to insert location data into database at an acceptable insertion rate. An enhanced adaptive location stream filtering algorithm (ALSF) based on the mobility pattern of moving objects, as well as several other filtering algorithms, are also introduced. Experiments with the simulated data show the performance advantage of the enhanced ALSF algorithm.