Abstract
Abstract The application of spatial joins for processing queries in spatial data streams is explored in this paper. Although their application has been studied in centralized and distributed systems, it has received little attention in spatial data streams. This work explores a particular issue with spatial join processing in spatial data streams - the lack of a bounded region of space from which the spatial objects are generated. Therefore, two strategies for join processing in spatial data streams in this situation are proposed. Both provide estimation of the common region shared by multiple spatial data streams to best process a spatial join between them. The strategies are evaluated and compared with a recently proposed approach. Results show that one strategy does an excellent job of estimating the common region given no existing bounded regions of space. Other results and future improvements are identified.
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