ar X iv : c s / 06 11 03 1 v 1 [ cs . D B ] 7 N ov 2 00 6 Efficient , Dynamic Indexing and Aggregation of Moving Objects

We present novel Max-Count, Threshold-Range, Threshold-Count, Threshold-Sum, ThresholdAverage and Count-Range estimation algorithms for d dimensions based on a new spatiotemporal index. Each query runs in constant time and is based on a skew aware indexing technique with static size buckets. This allows constant time inserts, deletes and updates for highly dynamic spatiotemporal databases. The technique is also decomposable to allow partial results to be calculated simultaneously and recombined in linear time. We performed extensive experiments which show that the Max-Count estimation algorithm runs up to 35 times faster than a precise algorithm with accuracy above 95%.