Continuous spatial query processing over clustered data set

Abstract

There exists an increasing usage rate of location-based information from mobile devices, which requires new query processing strategies. One such strategy is a moving (continuous) region query in which a moving user continuously sends queries to a central server to obtain data or information. In this thesis, we introduce two strategies to process a spatial moving query over clustered data sets. Both strategies utilize a validity region approach on the client in order to minimize the number of queries that are sent to the server. We explore the use of a two-dimensional indexing strategy, as well as the use of Expectation Maximization (EM) and k-means clustering. Our experiments show that both strategies outperform a Baseline strategy where all queries are sent to the server, with respect to data transmission, response time, and workload costs.