Publication Type

Conference Proceeding Article

Version

Postprint

Publication Date

3-2010

Abstract

Research on spatial network databases has so far considered that there is a single cost value associated with each road segment of the network. In most real-world situations, however, there may exist multiple cost types involved in transportation decision making. For example, the different costs of a road segment could be its Euclidean length, the driving time, the walking time, possible toll fee, etc. The relative significance of these cost types may vary from user to user. In this paper we consider such multi-cost transportation networks (MCN), where each edge (road segment) is associated with multiple cost values. We formulate skyline and top-k queries in MCNs and design algorithms for their efficient processing. Our solutions have two important properties in preference-based querying; the skyline methods are progressive and the top-k ones are incremental. The performance of our techniques is evaluated with experiments on a real road network.

Keywords

Cost values, Euclidean, Preference queries, Preference-based, Real road networks, Real world situations, Road segments, Spatial network database, Top-k query, Transportation decision making, Transportation network

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

ICDE 2010: IEEE 26th International Conference on Data Engineering: Proceedings, Long Beach, California, USA, 1 - 6 March 2010

First Page

533

Last Page

544

ISBN

9781424454457

Identifier

10.1109/ICDE.2010.5447851

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.ieeecomputersociety.org/10.1109/ICDE.2010.5447851

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