¿µ¹®³»¿ë (English Abstract) |
Multi-query optimization (MQO) is a critical research issue in the real-time data stream management system (DSMS). We propose to address this problem in the ubiquitous GIS (u-GIS) environment, focusing on grouping ¡®similar¡¯ spatio-temporal queries incrementally into N clusters so that they can be processed virtually as N queries. By minimizing N, the overlaps in the data requirements of the raw queries can be avoided, which implies the reducing of the total disk I/O cost. In this paper, we define the spatio-temporal query clustering problem and give a data cubing approach (Q-cube), which is expected to be implemented in the cloud computing paradigm. |