Abstract
Fast updates in spatial databases become a crucial issue in several application domains, such as LBS (location-based service). In particular, moving objects with frequent updates on their positions require fast update mechanisms in spatiotemporal database systems. In this paper, we propose a new method for the indexing of the current positions of moving objects on road network. Our method significantly improves not only the update cost but also the performance of query processing. The only constraint of our method is that the moving objects should be on roads, but we believe that most applications dealing moving objects imply this constraint. We provide a performance analysis on our model and by this we suggest further improvements on performance of our method. By experimental studies, we show that our method takes about 40% less in disk accesses compared to TPR-tree for updating and at maximum 4 times faster than TPR-tree for processing timestamp range queries.
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