Dynamic Reverse Furthest Neighbor Querying Technology Research Of Moving Objects

With the rapid development of wireless communication technology and global positioning technology, the application based on location service is experiencing unprecedented rapid development. Intelligent mobile terminals, vehicle navigation, such as positioning, and can be widely used in the GPS, Beidou, RFID, Bluetooth and other technology to achieve location sharing, and moving objects related services in many areas have demonstrated a broad application prospects. At present, moving objects database technology has been widely used in many fields, such as location based computing, geography, urban planning and network computing, and it is playing a more and more important role in solving some challenging scientific problems, so the spatial database has application prospects and potential value. With the increasing of the data sets of the moving objects and the structure of spatial data is increasingly complex, the effective query of the large number of moving objects in the spatial database becomes more and more important.Reverse furthest neighbor query is one of the methods of spatial database data query, which is a new query type based on reverse nearest neighbor query. Although currently on the reverse furthest neighbor query research rarely, it has a broad application prospect. The existing research of reverse furthest neighbor queries are mostly aimed at data points in a static environment query. With the widespread use of mobile devices and smart terminal, moving objects information increase gradually,which makes static revers furthest neighbor queries are unable to satisfy the requirements of dynamic queries. Based on the above, the paper studies dynamic reverse furthest neighbor querying problem of moving objects. Analysis and summary based on relevant research at home and abroad, put forward the dynamic reverse furthest neighbor querying algorithm of moving objects and probabilistic reverse furthest neighbor queries on uncertain moving objects. The main research work and contributions are summarized as follows:(1) In order to solve the weak influence of moving objects in related problems, the paper put forward a dynamic reverse furthest neighbor query algorithm. Algorithm to TPR-tree as the index structure, the use of half-plane pruning strategy, through the filter-refining the two step of the query object for efficient pruning. The experimental results show that the proposed algorithm is effective.(2) In order to effectively find the influence of querying large number of moving objects existing in boundary area vs querying results of global query area, we put forward probabilistic reverse furthest neighbor query algorithms. These algorithms can solve weak influence set of moving objects.In this paper, we study uncertain moving objects model and define spatial domination method and probabilistic reverse furthest neighbor query that is to retrieve the objects from the uncertain moving objects that have higher probability than a given threshold to be the reverse furthest neighbor of an uncertain query object. The experimental results show that the algorithm is correct.