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Benchmarking access methods for time-evolving regional data

机译:随时间变化的区域数据的基准访问方法

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In this paper we present a performance comparison of access methods for time-evolving regional data. Initially, we briefly review four temporal extensions of the Linear Region Quadtree: the Time-Split Linear Quadtree, the Multiversion Linear Quadtree, the Multiversion Access Structure for Evolving Raster Images and Overlapping Linear Quadtrees. These methods comprise a family of specialized access methods that can efficiently store and manipulate consecutive raster images. A new simpler implementation solution that provides efficient support for spatio-temporal queries referring to the past through these methods, is suggested. An extensive experimental space and time performance comparison of all the above access methods follows. The comparison is made under a common and flexible benchmarking environment in "order to choose the best technique depending on the application and on the image characteristics. These experimental results show that in most cases the Overlapping Linear Quadtrees method is the best choice.
机译:在本文中,我们介绍了随时间变化的区域数据的访问方法的性能比较。最初,我们简要回顾一下线性区域四叉树的四个时间扩展:时间分割线性四叉树,多版本线性四叉树,用于演化光栅图像的多版本访问结构和重叠线性四叉树。这些方法包括一系列专用的访问方法,可以有效地存储和处理连续的光栅图像。建议使用一种新的更简单的实现解决方案,通过这些方法为时空查询提供有效支持,以参考过去。下面是所有上述访问方法的广泛实验空间和时间性能比较。比较是在通用和灵活的基准测试环境下进行的,目的是“根据应用和图像特征选择最佳技术。这些实验结果表明,在大多数情况下,重叠线性四叉树方法是最佳选择。

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