Welfare Implications of the Transition to High Household Debt ∗

The generic framework for monitoring continuous spatial queries over moving objects addresses the location update issue and provides a common interface for monitoring mixed types of queries. It significantly reduces the wireless communication and query reevaluation costs required to maintain the up to-date query results. The papers suggest about the new algorithms and models to evaluate continuous queries in spatio temporal databases. A new query processing technique for dynamic queries over mobile objects is introduced. Continuous Nearest Neighbor CNN Search by performing a single query for the whole input segment. The CNN builds complex queries kCNN & trajectory NN queries and eliminates the false misses and the high processing cost, there by producing node accesses. The K-nearest neighbor search for moving query point is a progressive way which makes use of four different Algorithms are proposed for solving the problem that the query point is not static, as in k-nearest neighbor problem, but varies its position over time and parameters that effect the performance of algorithm are presented. Our algorithm always outperforms the existing ones by fetching 70% less disk pages. We use TPR model that accurately estimates the costs of predictive window queries, and quantifies the performance of spatio-temporal access methods. Then it presents the TPR*-tree, a new spatiotemporal access method highly optimized for moving data. Currently, all existing spatio-temporal access methods either aim at the past or the future, but not both. It would be interesting to develop a persistent version of the TPR*-tree, suitable for historical and future information retrieval. In such a tree, outdated versions of objects are not deleted, but kept separately. The Scalable On-Line Execution algorithm (SOLE) is presented as a spatio-temporal join between two input streams which are the spatio temporal objects and queries by utilizing a self-tuning approach based on load shedding. Generic and Progressive Algorithm for continuous mobile queries over mobile objects GPAC provides online, progressive, and fast response to continuous spatiotemporal queries. Multi predicate spatio-temporal queries requires special handling and cannot be efficiently answered by simply stacking existing spatio-temporal operators on top of each other to form a pipeline. It is crucial to consider adaptive query optimization techniques when dealing with spatio temporal data stream management systems. A large spectrum of research has been devoted to continuous spatio-temporal query processing. However, we argue that several outstanding challenges have been either addressed partially or not at all in the existing literature.