Kinetic Data Structures:Querying Moving Objects

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Querying Moving Objects

Continuous tracking of a geometric attribute may be more than is needed for some applications. There may be time intervals during which the value of the attribute is of no interest; in other scenarios we may be just interested to know the attribute value at certain discrete query times. For example, given n moving points in 2, we may want to pose queries asking for all points inside a rectangle R at time t, for various values of R and t, or for an interval of time ∆t, etc. Such problems can be handled by a mixture of kinetic and static techniques, including standard range-searching tools such as partition trees and range trees [21]. They typically involve tradeoffs between evolving indices kinetically, or prebuilding indices for static snapshots. An especially interesting special case is when we want to be able answer queries about the near future faster than those about the distant future—a natural desideratum in many real-time applications.

A number of other classical range-searching structures, such as k-d-trees and R-trees have recently been investigated for moving objects [1, 2].

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