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# Explicit and Implicit Constrained-Space Probabilistic Threshold Range Queries for Moving Objects

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### Abstract

This paper studies the constrained-space probabilistic threshold range query (CSPTRQ) for moving objects. We differentiate two kinds of CSPTRQs: implicit and explicit ones. Specifically, for each moving object $$o$$, we assume $$o$$ cannot be located in some specific areas, we model its location as a closed region, $$u$$, together with a probability density function, and model a query range, $$R$$, as an arbitrary polygon. An implicit CSPTRQ can be reduced to a search (over all the $$u$$) that returns a set of objects, which have probabilities higher than a probability threshold $$p_t$$ to be located in $$R$$, where $$0\leq p_t\leq 1$$. In contrast, an explicit CSPTRQ returns a set of tuples in form of ($$o$$, $$p$$) such that $$p\geq p_t$$, where $$p$$ is the probability of $$o$$ being located in $$R$$. A straightforward adaptation of existing method is inefficient due to its weak pruning/validating capability. In order to efficiently process such queries, we propose targeted solutions, in which three main ideas are incorporated: (1) swapping the order of geometric operations based on the computation duality; (2) pruning unrelated objects in the early stages using the location unreachability; and (3) computing the probability using the multi-step mechanism. Extensive experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.

### Most cited references28

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### Managing uncertainty in moving objects databases

(2004)
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### Capturing the Uncertainty of Moving-Object Representations

(1999)
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### Querying imprecise data in moving object environments

(2004)
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### Author and article information

###### Journal
01 November 2013
2013-12-04
###### Article
1311.0320
4650515d-f7bf-4cbe-9798-c07ef3b41893