I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. In EDBT Conference, 2002.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....of a trajectory into segments. A partially persistent tree structure [5, 18] is used to index the data. This approach generalizes a previous work [4] in which it was assumed that the objects move with a linear function of time, whereas in [7] more complex functions are permitted. Porkaew et al. [15, 6] examine the indexing of trajectories in Native Space (cf. Section 2.1) vs. Parametric Space. In Parametric Space, segments of trajectories are represented in terms of a location and a motion vector. In their experimental evaluation, the authors use an R tree structure as an index for both ....

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. In Proceedings of the 8th International Conference on Extending Database Technology, pages 269--286, 2002.

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I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. In EDBT Conference, 2002.

....motivation is to improve system performance, rather than regression analysis. A useful extension to our work would be to use some of the ideas in [5] to address correlations between multiple time series that a single sensor may be monitoring. Finally, we refer to work in moving object databases [28, 25, 19]. In this research field, we find the idea of approximating the time series of an object s location without continuous updates, in Wolfson et al. 28] of predicting an object s future location based on its velocity vector in Saltenis et al. 25] and of using the predictability of motion for ....

.... idea of approximating the time series of an object s location without continuous updates, in Wolfson et al. 28] of predicting an object s future location based on its velocity vector in Saltenis et al. 25] and of using the predictability of motion for improving performance in Lazaridis et al. [19]. 7. Conclusions In this paper we motivate the importance of capturing time series generated by wireless sensors. To achieve this we task sensors with compressing time series and fitting predictive models. We propose an optimal online algorithm for creating the piecewise constant approximation ....

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. In EDBT Conference, 2002.

....motivation is to improve system performance, rather than regression analysis. A useful extension to our work would be to use some of the ideas in [5] to address correlations between multiple time series that a single sensor may be monitoring. Finally, we refer to work in moving object databases [28, 25, 19]. In this research field, we find the idea of approximating the time series of an object s location without continuous updates, in Wolfson et al. 28] of predicting an object s future location based on its velocity vector in Saltenis et al. 25] and of using the predictability of motion for ....

.... idea of approximating the time series of an object s location without continuous updates, in Wolfson et al. 28] of predicting an object s future location based on its velocity vector in Saltenis et al. 25] and of using the predictability of motion for improving performance in Lazaridis et al. [19]. 7. Conclusions In this paper we motivate the importance of capturing time series generated by wireless sensors. To achieve this we task sensors with compressing time series and fitting predictive models. We propose an optimal online algorithm for creating the piecewise constant approximation ....

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. In EDBT Conference, 2002.

....similar to the bounding boxes in internal nodes, we can compute T i by checking the four cases. The geometric intuition for computing the intersection of both motion segments and bounding boxes with the query trajectory is fairly simple. To conserve space, we give the precise formulae in [9]. The bene t of this over the naive approach (in which each snapshot query is independently evaluated) is that we access each R tree node at most once irrespective of the frame rate (snapshot rate) that the application attempts to render. In the naive approach, each frame corresponds to a ....

....the query processor will check each bounding box (starting from that of the root node) if it is discardable. A bounding box R is discardable i the overlapping part of R and Q is covered by P . Otherwise, the node corresponding to the box R needs to be explored. The following lemma (proven in [9]) formalizes the condition when a given node R of a data structure is discardable. Lemma 1 (Discardable) Let Q be the current query box and P be the previous one. Let R be a bounding box corresponding to an R tree node. R is discardable i (Q R) P . The search algorithm for NPDQ works as ....

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I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. (full version) Technical Report TR-DB-01-07, UC Irvine, 2001.

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Iosif Lazaridis, Kriengkrai Porkaew, and Sharad Mehrotra. Dynamic queries over mobile objects. In EDBT, 2002. 49

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I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. In EDBT, 2002.

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Iosif Lazaridis, Kriengkrai Porkaew, and Sharad Mehrotra. Dynamic Queries over Mobile Objects. In EDBT, 2002.

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I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic Queries over Mobile Objects. In EDBT, 2002.

No context found.

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic Queries over Mobile Objects. In EDBT, 2002.

No context found.

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic Queries over Mobile Objects. In EDBT, 2002.

No context found.

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic queries over mobile objects. In Proc. of 8th Intl. Conf. on Extending Database Technology, pages 269--286, 2002.

No context found.

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic Queries over Mobile Objects. In Proceedings of the 8th Intern. Conf. on Extending Database Technology, pages 269--286, 2002.

No context found.

I. Lazaridis, K. Porkaew, and S. Mehrotra. Dynamic Queries over Mobile Objects. In EDBT, 2002.

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