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A Novel Query Method for Spatial Data in Mobile Cloud Computing Environment

机译:移动云计算环境中空间数据查询的新方法

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With the development of network communication, a 1000-fold increase in traffic demand from 4G to 5G, it is critical to provide efficient and fast spatial data access interface for applications in mobile environment. In view of the low I/O efficiency and high latency of existing methods, this paper presents a memory-based spatial data query method that uses the distributed memory file system Alluxio to store data and build a two-level index based on the Alluxio key-value structure; moreover, it aims to solve the problem of low efficiency of traditional method; according to the characteristics of Spark computing framework, a data input format for spatial data query is proposed, which can selectively read the file data and reduce the data I/O. The comparative experiments show that the memory-based file system Alluxio has better I/O performance than the disk file system; compared with the traditional distributed query method, the method we proposed reduces the retrieval time greatly.
机译:随着网络通信的发展,从4G到5G的流量需求增长了1000倍,为移动环境中的应用提供高效,快速的空间数据访问接口至关重要。鉴于现有方法的低I / O效率和高延迟,本文提出了一种基于内存的空间数据查询方法,该方法使用分布式内存文件系统Alluxio来存储数据并基于Alluxio键构建一个二级索引价值结构;此外,其目的在于解决传统方法效率低的问题。根据Spark计算框架的特点,提出一种空间数据查询的数据输入格式,可以选择性地读取文件数据,减少数据I / O。对比实验表明,基于内存的文件系统Alluxio具有比磁盘文件系统更好的I / O性能。与传统的分布式查询方法相比,本文提出的方法大大减少了检索时间。

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