Moving Objects Based On Temporal And Spatial Database Indexing Techniques And Realization

Spatio-temporal database technology is new field of computer science, with the rapid development of mobile communication technology, mobile information services have been concerned, and it has become feasible and necessary to tracking and location moving objects. In order to effectively manage vast amounts of data in the database, moving object indexing techniques appeared, it can effectively query, and manage the moving objects and provide accurate location-based services. Indexing moving objects in spatio-temporal database research has important significance.On the basis of introducing the spatio-tamporal database technology and moving objects index, compare the existing classification Indexing moving objects, discuss the characteristic of moving objects in discrete, and focus on Kwon's LUR-Tree. LUR-Tree (Lazy Update R-Tree) is based on R-Tree index structure for moving objects, only when the object out of the MBR, it updates the corresponding index structure to reduce the updating cost; the same time, the introduction of extend MBR (EMBR) to reduce more updating cost. But this approach would make the overlap area of internal nodes increased, leading to a decline in the efficiency of the query; LUR-Tree only concerned about the current location of the object, Once the location of the object update, its old record will be deleted, new record are inserted. So it can not satisfy the query on the recent historical information.Hence we improve the discrete moving objects index, and present space storage with consecutive trace and a novel indexing structure called QLUR+-tree (Quad Lazy Update R+-tree), which can simultaneously index historical and current information. It combines R+-tree and Quad-tree, using the R+-tree to index current information of moving objects, and the quadtree to store and index history information of moving objects. Combining with the lazy update algorithm of LUR-tree, we propose the update strategy of dynamic contraction and expansion of MBR. A secondary index structure was used to achieve information transition, and improve the algorithm of insert, update and query of the index. Through the theoretical analysis and experiments, QLUR+-tree indexing structure can improve the efficiency of the point query and the domain queries of the entire space while maintaining a low updating cost and disk overhead.