Adaptive cell-based index for moving objects

摘要

R-tree based access methods for moving objects are hardly applicable in practice, due mainly to excessive space requirements and high management costs. To overcome the limitations of such R-tree based access methods, we propose a new index structure called AIM (Adaptive cell-based Index for Moving objects). The AIM is a cell-based multiversion access structure adopting an overlapping technique. The AIM refines cells adaptively to handle regional data skew, which may change its locations over time. Through the extensive performance studies, we observed that The AIM consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with R-tree based methods.