Indexing of Moving Objects in a Constrained Network
一种基于受限网络的移动对象索引

Advance in wireless sensor networks and positioning technologies enable new data management applications to monitor continuous streaming data. An efficient indexing structure for moving objects is necessary for supporting the query processing of these dynamic data I}his paper proposed a new index technique based on a simulation prediction model,which supported ctuerying the past, present and future positions of moving objects in urban traffic networks.First,making full use of the feature of urban traffic networks,we used cellular automata model with crossings to simulate the movements of the objects. Then, by linear regression and circular are fragmented curve-fitting, the prediction trajectory equation of the objects in regular road segment and in crossing could be obtained. Moreover, we presented a dynamic structure named AU(adaptive units) which grouped neighbor objects moving in the similar moving patterns and developed it a two levels R-tree and a link list based index named AUC(Adaptive Unit Compounding) index. Finally, experimental studies indicated that the AUC index outperformed TPR-tree and TB-tree.