Abstract
With the proliferation of mobile computing, the ability to index
efficiently the movements of mobile objects becomes important. Objects are
typically seen as moving in two-dimensional (x,y) space, which means that their
movements across time may be embedded in the three-dimensional (x,y,t) space.
Further, the movements are typically represented as trajectories, sequences of
connected line segments. In certain cases, movement is restricted, and
specifically in this paper, we aim at exploiting that movements occur in
transportation networks to reduce the dimensionality of the data. Briefly, the
idea is to reduce movements to occur in one spatial dimension. As a consequence,
the movement data becomes two-dimensional (x,t). The advantages of considering
such lower-dimensional trajectories are the reduced overall size of the data and
the lower-dimensional indexing challenge. Since off-the-shelf database
management systems typically do not offer higher-dimensional indexing, this
reduction in dimensionality allows us to use such DBM- Ses to store and index
trajectories. Moreover, we argue that, given the right circumstances, indexing
these dimensionality-reduced trajectories can be more efficient than using a
three-dimensional index. This hypothesis is verified by an experimental study
that incorporates trajectories stemming from real and synthetic road
networks.
Originalsprog | Engelsk |
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Titel | Proceedings of the Eleventh International Symposium on Advances in Geographic Information Systems, New Orleans, LA November 78 |
Publikationsdato | 2003 |
Status | Udgivet - 2003 |
Begivenhed | Indexing of Network-Constrained Moving Objects - Varighed: 19 maj 2010 → … |
Konference
Konference | Indexing of Network-Constrained Moving Objects |
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Periode | 19/05/2010 → … |
Bibliografisk note
ISSN ; -Emneord
- indexing moving objects
- Spatiotemporal databases
- moving object databases
- indexing network data