aCN-RB-tree: Constrained Network-Based Index for Spatio-Temporal Aggregation of Moving Object Trajectory
Dong Wook Lee · KSII Transactions on Internet and Information Systems · 2009
Moving object management is widely used in traffic, logistic and data mining applications in ubiquitous environments.It is required to analyze spatio-temporal data and trajectories for moving object management.In this paper, we proposed a novel index structure for spatio-temporal aggregation of trajectory in a constrained network, named aCN-RB-tree.It manages aggregation values of trajectories using a constraint network-based index and it also supports direction of trajectory.An aCN-RB-tree consists of an aR-tree in its center and an extended B-tree.In this structure, an aR-tree is similar to a Min/Max R-tree, which stores the child nodes' max aggregation value in the parent node.Also, the proposed index structure is based on a constrained network structure such as a FNR-tree, so that it can decrease the dead space of index nodes.Each leaf node of an aR-tree has an extended B-tree which can store timestamp-based aggregation values.As it considers the direction of trajectory, the extended B-tree has a structure with direction.So this kind of aCN-RB-tree index can support efficient search for trajectory and traffic zone.The aCN-RB-tree can find a moving object trajectory in a given time interval efficiently.It can support traffic management systems and mining systems in ubiquitous environments.