Proximity Relation Processing With Evolving Environment

An important problem for many location-based applications is the continuous evaluation of proximity relations among moving objects. These relations express whether a given set of objects is in a spatial constellation or in a spatial constellation relative to a given point of demarcation in the environment. The challenge lies in the continuous processing of large numbers of such relations as the location position information of the objects change. In this paper, we propose an adaptive location constraint indexing technique for solving this problem. The proposed indexing technique adapts well to the change of movement patterns of the mobile objects, stabilizes the system performance, and reduces the cost for continuously processing the proximity relations for both in-memory processing and for I/O-incurring environment.

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