Multi-criteria optimization in GIS: Continuous K-nearest neighbor search in mobile navigation

The generalization of existing spatial data for cartographic production can be expressed as optimizing both the amount of information to be presented, and the legibility/usability of the final map, while conserving data accuracy, geographic characteristics, and aesthetical quality. As an application of information system optimization, distributed wireless mobile network serves as the underlying infrastructure to digital ecosystems. It provides important applications to the digital ecosystems, one of which is mobile navigations and continuous mobile information services. Most information and query services in a mobile environment are continuous mobile query processing or continuous k nearest neighbor (CKNN), which finds the locations where interest points or interest objects change while mobile users are moving. In this paper, we propose a neural network based algorithm solution for continuous k nearest neighbor (CKNN) search in such a system which divides the query path into segments and improves the overall query process.