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Indexing And Querying Techniques For The Past, The Present And The Future Information Of Moving Objects

Posted on:2007-07-28Degree:MasterType:Thesis
Country:ChinaCandidate:W J ZhangFull Text:PDF
GTID:2178360185985594Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
With the development of positioning technology and wireless communication techniques, tracking the position of moving objects becomes increasingly feasible and necessary. The management of moving objects has application background in many fields including traffic control, boats navigating, dynamic computing, weather forecast, digital battlefield, etc. The position of moving objects changes continuously over time and historical information of moving objects includes both spatial and temporal aspects. Such characteristics make it inapplicable to support efficient management of moving object information with traditional database techniques, so moving object database techniques are introduced. So far although large number of methods that focus explicitly on historical information retrieval or future prediction has been proposed, little attention has been given to the development of indexes that efficiently support queries about the past, the present and the anticipated future positions of moving objects.In this paper, our research focus is to support queries about the past, the present and the future in moving object database. The contribution includes following three aspects:(1) Index structure TB_PPF-index is proposed to support queries about the past, the present and the future. TB_PPF-index is able to support trajectory based queries about the historical information of moving objects. First, the historical trajectories of moving objects are indexed by TB-tree after trajectory splitting. A buffer containing the latest trajectory segment is maintained for each moving object to support trajectory splitting. Second, TB_TPR-tree is proposed to index the current and anticipated future positions of moving objects, meanwhile supports the management of trajectory segment in the buffer. Query-processing algorithm for the past, the present and the future positions is proposed based on TB_PPF-index.(2) Index structure CB_PPF-index is proposed to efficiently support query processing about the past, the present and the future positions of moving objects. Optimized index structure E3D R-tree based on 3D R-tree is proposed to support historical queries. E3D R-tree takes into account the features of moving object data and takes advantage of new cost parameters. In particular, least-cost-first search algorithm is used in the insertion algorithm to find the overall best way to insert a new record in E3D R-tree. The proof of the vidility of the algorithm is given. The result of experiments illustrates that E3D R-tree outperforms 3D R-tree in query processing. Index structure ATPR-tree which supports asynchronous update of moving objects is proposed to process queries about the present and the anticipated future information In...
Keywords/Search Tags:moving object database, query, index, complex spatio-temporal pattern query
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