CAREER: Fast Query Support for Emerging Spatial Database Applications

Grant: NSF CAREER Award IIS-0347600.
Duration: July 2004 to June 2009.
Amount: $506,000.
PI: Donghui Zhang (CCIS, Northeastern University).
Funding Agency: National Science Foundation.

Project 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, yet fast query response is anticipated. This project examines efficient query processing in spatial databases. In particular, we consider 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 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 instance, 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 instance, 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 faster query processing algorithms, the end users will benefit from the proposed research. The project also has a strong educational focus. We provide a modern curriculum which is based on not only providing the students with textbook knowledge and hands-on practice, but involving them early in research.

Supported students

The project has supported two Ph.D. students: Tian Xia, Yang Du, Ling Hu.

Developed courses

Data Mining Techniques
Implementation of Database Systems
Algorithms in Spatial Databases and Computational Geometry

Supported trips

The project has supported the PI and his students to attend the following conferences to disseminate results: ICDE'08 in Cancun, Mexico; GIS'07 in Seattle, WA; SIGMOD'07 in Beijing, China; SIGMOD'06 in Chicago; ICDE'07 in Istanbul, Turkey; ICDE'06 in Atlanta, Georgia; VLDB'06 in Seoul, Korea; VLDB'05 in Trondheim, Norway; SSTD'05 in Angra dos Reis, Brazil.

Highlights of Findings:


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