CAREER: Fast Query Support for Emerging Spatial Database Applications

Northeastern University, Boston MA

Investigators

Abstract

Spatial databases and Geographic Information Systems (GIS) have many applications. Examples include environmental systems, corporate decision-support systems, travel arrangement systems, etc. Typically, such applications have large volumes of data, with a critical need for fast query response. This project examines efficient query processing in spatial databases. In particular, the research focuses on the selection query, the aggregation query and the proximity query. The selection query finds the objects in a user-specified region. For instance, find objects in the Washington, DC area. This project examines novel techniques that are more efficient than existing approaches. The aggregation query computes some aggregate information in a user-specified region, for example: find the total number of restaurants in a given region, find the total precipitation of rainfall in New York State over the past year, etc. Here enumerating the actual objects is not required for answering the query. This project designs algorithms with sub-linear query cost. The proximity query finds interesting results based on the closeness of objects, for example: find a hotel/library pair which are the closest to each other, find a location for a potential supermarket which will be close to maximum number of residents, find an apartment whose weighted total distance to a supermarket and a subway station is minimal. The project will advance the spatial database technology, and will have an impact on many fields that deal with spatial data. When systems in such fields are equipped with more expressive query features and faster query processing algorithms, the end users will benefit from the research results. The project also has a strong educational focus, including a modern curriculum which is based on not only providing the students with textbook knowledge and hands-on practice, but involving them in research. The project Web site http://www.ccs.neu.edu/home/donghui/research/CAREER_grant will be used to disseminate the published papers, and the system integration and the experimental results.