Incremental k-Nearest-Neighbor Search on Road Networks

Most query search on road networks is either to find objects within a certain range (range search) or to find K nearest neighbors (KNN) on the actual road network map. In this paper, we propose a novel query, that is, incremental k nearest neighbor (iKNN). iKNN can be defined as given a set of candidate interest objects, a query point and the number of objects k, find a path which starts at the query point, goes through k interest objects and the distance of this path is the shortest among all possible paths. This is a new type of query, which can be used when we want to visit k interest objects one by one from the query point. This approach is based on expanding the network from the query point, keeping the results in a query set and updating the query set when reaching network intersection or interest objects. The basic theory of this approach is Dijkstra's algorithm and the Incremental Network Expansion (INE) algorithm. Our experiment verified the applicability of the proposed approach to solve the queries, which involve finding incremental k nearest neighbor.

[1]  David Taniar,et al.  A Taxonomy of Indexing Schemes for Parallel Database Systems , 2002, Distributed and Parallel Databases.

[2]  Haibo Hu,et al.  When location-based services meet databases , 2005, Mob. Inf. Syst..

[3]  Maytham Safar,et al.  K nearest neighbor search in navigation systems , 2005, Mob. Inf. Syst..

[4]  David Taniar,et al.  Optimal Broadcast Channel for Data Dissemination in Mobile Database Environment , 2003, APPT.

[5]  David Taniar,et al.  Research in mobile database query optimization and processing , 2005, Mob. Inf. Syst..

[6]  J. Wenny Rahayu,et al.  Global parallel index for multi-processors database systems , 2004, Inf. Sci..

[7]  Cyrus Shahabi,et al.  Alternative Solutions for Continuous K Nearest Neighbor Queries in Spatial Network Databases , 2005, STDBM.

[8]  David Taniar,et al.  A taxonomy of broadcast indexing schemes for multi channel data dissemination in mobile databases , 2004, 18th International Conference on Advanced Information Networking and Applications, 2004. AINA 2004..

[9]  Maytham Safar,et al.  eDAR Algorithm for Continuous KNN Queries Based on Pine , 2006, Int. J. Inf. Technol. Web Eng..

[10]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[11]  David Taniar,et al.  Data retrieval for location-dependent queries in a multi-cell wireless environment , 2005, Mob. Inf. Syst..

[12]  Karine Zeitouni,et al.  GeoCache: A Cache for GML Geographical Data , 2007, Int. J. Data Warehous. Min..

[13]  Tuoi Thi Phan,et al.  A hybrid solution of ontology-based query expansion , 2008, Int. J. Web Inf. Syst..

[14]  Stephen R. Gulliver,et al.  A context-aware Tour Guide: User implications , 2007, Mob. Inf. Syst..

[15]  Antonin Guttman,et al.  R-trees: a dynamic index structure for spatial searching , 1984, SIGMOD '84.

[16]  David A. Gadish Introducing the Elasticity of Spatial Data , 2008, Int. J. Data Warehous. Min..