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A novel method to manage very large raster data on distributed key-value storage system

机译:一种在分布式键值存储系统上管理非常大的栅格数据的新方法

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With the rapid development of information technologies and GIS techniques, raster data amount is growing on an unprecedented scale. Existing WebGIS based on local file systems and RDBMS cannot manage very large raster data efficiently because of limited storage capacity of single node. Although expensive storage devices are used to enlarge capacity, WebGIS is still vulnerable to suffer from single point of failure for its poor scalability. We propose a novel method to manage very large raster data, it has three characteristics. Firstly, raster data management system is built upon distributed key-value storage system instead of local file system and RDBMS, it has good scalability and high availability. Secondly, revised quadtree-based raster index is built in system to improve access efficiency. Thirdly, our prototype is transparent to WebGIS applications, and hence can integrate with existing applications seamlessly. The experimental results show that our method outperforms existing methods.
机译:随着信息技术和GIS技术的飞速发展,栅格数据量正以前所未有的速度增长。由于单个节点的存储容量有限,基于本地文件系统和RDBMS的现有WebGIS无法有效地管理非常大的栅格数据。尽管使用昂贵的存储设备来扩展容量,但WebGIS仍因其可扩展性差而容易遭受单点故障的困扰。我们提出了一种管理非常大的栅格数据的新颖方法,它具有三个特点。首先,栅格数据管理系统建立在分布式键值存储系统上,而不是本地文件系统和RDBMS之上,具有良好的可扩展性和高可用性。其次,在系统中内置了基于四叉树的改进的栅格索引,以提高访问效率。第三,我们的原型对WebGIS应用程序是透明的,因此可以与现有应用程序无缝集成。实验结果表明,我们的方法优于现有方法。

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