Motion data index structure: an efficient indexing for spatio-temporal data of moving objects

The spatial and temporal characteristics of the data used to describe moving objects' movement make them large in quantity and complex to manage. Different queries to motion data ask for various organization methods. According to the needs of most applications, general motion model is used to represent the translation and rotation of moving objects during a period of time. Because the motion data are multidimensional in space and time dimension, 2(n) tree is employed to construct the main part of the index to these data. Meanwhile other kinds of index algorithms should be added to the index structure so as to meet the needs of queries other than state queries only related to a specific epoch. Thus, motion data index structure (MDIS) is constructed as a multi-entry multi-level index structure for the organization of motion data. Each index within MDIS may work alone or cooperate with each other to process different kinds of queries. The extra space needed for MDIS is only about 5%similar to 6% of the total storage space of motion data themselves. And the respond time to each query is much decreased and acceptable to most applications dealing with moving objects.