A Nearest Neighbor Query Method Of Moving Objects With Uncertainty In Constrained Networks

Nearest neighbor query of moving objects in constrained network environment has important and widely practical significance, in air transporants management, transportation programming,GIS,mobile computation and location-based electronic commerce etc. Uncertainty is inherent aspect of moving objects.The processing of uncertainty is an important research in the space-time moving objects database. Whether effectivly capture the uncertainty of moving objects movement in the query, will directly affect the accuracy of the search results.The index structures is the key technology of continuous query to realize trajectory。for the position of moving objects continuously changing characteristics over time, studying the moving objects trajectory model establishment, updating of the object trajectory storage and the uncertainty inquires problem of trajectory is more important. On the basis of establishing the correct constrained network mobile object model and indexing structure, we discuss the uncertainty of moving objects nearest inquires.This paper firstly introduces constrained network,moving object and other basic concepts. Study analyzed the key technology of R tree, TPR index structures, and the moving objects database query, for moving objects database objects in the nearest inquires the research work track lay a theoretical basis. An existed uncertain trajectory model is adapted when nearest neighbor query is preformed with uncertainty considered. Given the model, a method of networks influence region gradually expansion of query object is proposed to compute the probability that the candidate object will be the nearest neighbor of given query object.Finally, simulation experiments of this algorithm are analyzed and studied, the result shows that the algorithm is more feasible and effective, improving the accuracy of the query result.