Research On Spatial Data Search Method Based On Top-k

With the rapid growth of the spatial data management technology, spatial data search,which is one of the most important operations has been researched deeply, which is one of the most important operations. Especially the commercialization of the 3G mobile communication standard like WCDMA and TD-SCDMA and the popularization of smart mobile devices boosted the application of spatial data search technology on the aspect of Location Based Service. Top-k search in road network environment, which is the most important search method of spatial data search, attracted industry's attention widely.The efficiency of Top-k search algorithm is the most important criteria of its search performance. Despite some scholars have already undertaken researches on this aspect and have achieved some result. But the search points are always dynamic in reality, and the efficiency of naive snapshot solution is always low when processing the Top-k search of dynamic point. Besides this,a large amount of search request could always be received by the server simultaneously. The efficiency of traditional method is too low to process this circumstance. So we proposed TKSCS, a new solution for solving Top-k spatial search in road network based on traditional snapshot search method.The proposed method utilized the concept of Safe Segment to reduce the frequent communication between the client and server, lead to release the network burden and the redundant computations. Then, the method used an expansion tree to avoid unnecessary traversing of some network edges, enhanced the Top-k searching performance. Beside this,according to the feature of spatial search in road network circumstance, the method added a density score of relevant object into top-k evaluation criteria.Experimental evaluation using large real datasets demonstrates that the proposed methods both outperform baseline methods significantly.