Uncertainty Management for Network Constrained Moving Objects

Uncertainty Management for Network Constrained Moving Objects

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Unformatted text preview: Uncertainty Management for Network Constrained Moving Objects * Zhiming Ding and Ralf Hartmut Gting Praktische Informatik IV Fernuniversitt Hagen, D-58084 Hagen, Germany {zhiming.ding, rhg}@fernuni-hagen.de Abstract. One of the key research issues with moving objects databases (MOD) is the uncertainty management problem. In this paper, we discuss how the un- certainty of network constrained moving objects can be reduced by using rea- sonable modeling methods and location update policies. Besides, we present a framework to support variable accuracies in presenting the locations of moving objects. The operation design issues with uncertainty involved are also dis- cussed. 1. Introduction Uncertainty management is an important research issue in the moving objects database (MOD) technology. As stated in [8, 13], due to network delays, measuring errors, and the limitations of sampling methods, uncertainty is an inherent aspect of MOD. The uncertainty management problem in MOD is actually two-fold first, how to reduce uncertainty through reasonable modeling methods and location update policies; and second, how to express uncertainty and deal with uncertain data in databases by introducing suitable data types, operations, and index structures. In recent years, a lot of research has been focused on the uncertainty management problem for moving objects, especially on the second aspect of the problem. In [8], Pfoser and Jensen et al. have analyzed the sources of uncertainty in presenting the locations of moving objects, and a representation framework has been proposed to deal with uncertain data. The work in [9] has explored the uncertainty and fuzziness in managing moving objects, and a mechanism is provided to deal with temporal, spatial, and spatio-temporal indeterminacies. In [12, 13], Trajcevski and Wolfson et al. have discussed the uncertainty management strategies in the DOMINO system. By applying an uncertainty threshold, the trajectory of a moving object is extended from a curve to a tube in the X % Y % T space and the operations, such as inside , are extended by intro- ducing the uncertainty semantics such as sometimes, always, possibly, and definitely. In [11], a set of data types and operations have been proposed for the uncertainty management of moving objects. However, nearly none of these works have treated the interactions between moving objects and the underlying transporta- tion networks in anyway. The works in [4, 7, 10] have discussed the uncertainty man- * This research was supported by the Deutsche Forschungsgemeinschaft (DFG) research project Data- bases for Moving Objects under grant number Gu293/8-1. agement problems with transportation networks involved. However, transportation networks are only used to reduce sampling noises from GPS or to predict future posi- tions of moving objects....
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Uncertainty Management for Network Constrained Moving Objects

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