IEEE Transactions on Computers
On the Generation of Spatiotemporal Datasets
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Efficient Evaluation of Continuous Range Queries on Moving Objects
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
SINA: scalable incremental processing of continuous queries in spatio-temporal databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Supporting frequent updates in R-trees: a bottom-up approach
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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Continuous range monitoring on moving objects has been increasingly important in mobile environments. With the computational power and memory capacity on the mobile side, the distributed processing could relieve the server from high workload and provide real-time results. The existing distributed approaches typically partition the space into subspaces and associate the monitoring regions with those subspaces. However, the spatial irrelevance of the subspaces and the monitoring regions incurs the redundant processing as well as the extra communication cost. In this paper, we propose continuous expansion (CEM), a novel approach for efficient processing of continuous range monitoring in mobile environments. Considering the concurrent execution of multiple continuous range queries, CEM abstracts the dynamic relations between the movement of objects and the change of query answers, and introduces the concept of query view. The query answers are affected if and only if there are objects changing their current query views, which lead to the minimum transmission cost on the moving object side. CEM eliminates the redundant processing by handling the updates only from the objects that potentially change the answers. The experimental results show that CEM achieves the good performance in terms of server load and communication cost.