Recursive partitioning method for trajectory indexing

A trajectory is defined as the record of time-varying spatial phenomenon. The trajectory database is an important research area that has received a lot of interest in the last decade, with the objective of trajectory databases being to extend existing database technology to support the representation and querying of moving objects and their trajectories. Querying in trajectory databases can be very expensive due to the nature of the data and the complexity of the query processing algorithms. Given also that location-aware devices, like the GPS, are present everywhere these days, trajectory databases will soon face an enormous amount of data. Consequently the performance in the presence of a vast amount of data will be a significant problem and efficient indexing schemes are required to support both updates and searches efficiently. This paper provides the methodology for using the recursive partitioning technique for indexing trajectories in the unrestricted space, which is called the Recursively Partitioned Trajectory Index (RPTI). RPTI uses the two-level indexing structure, as does the state of art indexing scheme, SETI, and maintains separate indices for the space and time dimensions. We present the algorithms for constructing the RPTI and the algorithms for updates that include insertion and deletion. We also provide the results of the experimental study on the RPTI and have demonstrated that RPTI is better than SETI in handling trajectory-based queries and is competitive with SETI in handling coordinate-based queries. The structure of RPTI can be easily implemented by using any of the existing spatial indexing structures. The only design parameters required are the standard disk page size and maximum level of recursive partitioning.