DTNH Indexing Method: Past Present and Future Data Prediction for Spatio-Temporal Data
John Ayeelyan, Sugumarn Muthukumarasamy, R.S. Rajesh · International journal of intelligent engineering and systems · 2017
Indexing methods are developed to effectively process user queries in many real-time and moving object management applications.The existing spatial data updating indexing methods are based on the Integrated binary Tree, R-Tree, R*-Tree, Oct-Tree, Quad-Tree, Grid-Tree and Hex-Tree.The depth of these trees is unbalanced and overlapping, hence the performance is reduced in the multi-structure indexing methods.D-Tree (Decompose -Tree) based multi-structure spatio-temporal index method is proposed to find the present, past and future data.The new multistructural model called DTNH-Tree used to find the present, past and future data.It consists of D-Tree, TB*-Tree, NT-Tree and hash table.The D-Tree indexing is used to get the spatial data and manage the moving objects in the road network.A set of TB*-Tree is used to index the history of moving object on road networks.A set of NT -Trees is used to manage the current position of the recently updated data and find present data of the moving objects.NT-Tree indexes the present and future information of the moving objects.Finally the set of hash tables is used for updating the data continuously.The proposed multi-structure indexing method supports different types of query processing compared to the existing indexing methods.Experimental results exhibits better updation and query performance compared to the MSMON-Tree and PPF*-Tree.