北京航空航天大学学报 ›› 2019, Vol. 45 ›› Issue (1): 130-140.doi: 10.13700/j.bh.1001-5965.2018.0174

• 论文 • 上一篇    下一篇

一种面向工业互联网的云存储方法

孟祥曦1, 张凌2, 郭皓明3, 郭黎敏3, 夏乾臣1, 吕江花1, 马世龙1   

  1. 1. 北京航空航天大学 计算机学院, 北京 100083;
    2. 中国地震应急搜救中心, 北京 100049;
    3. 中国科学院软件研究所, 北京 100190
  • 收稿日期:2018-04-02 修回日期:2018-09-03 出版日期:2019-01-20 发布日期:2019-01-28
  • 通讯作者: 张凌 E-mail:zhangling903@163.com
  • 作者简介:孟祥曦,男,博士研究生。主要研究方向:数据管理系统、模型管理、软件工程;张凌,男,高级工程师。主要研究方向:大数据管理与应用、自动化测试、大数据分析;郭皓明,男,博士,高级工程师。主要研究方向:软件测试、形式化方法与软件工程,大数据管理与应用。
  • 基金资助:
    国家自然科学基金(61300007,61305054);软件开发环境国家重点实验室自主探索基金(SKLSDE-2012ZX-28,SKLSDE-2014ZX-06)

A new approach of cloud storage for industrial Internet

MENG Xiangxi1, ZHANG Ling2, GUO Haoming3, GUO Limin3, XIA Qianchen1, LYU Jianghua1, MA Shilong1   

  1. 1. School of Computer Science and Engineering, Beihang University, Beijing 100083, China;
    2. National Earthquake Response Support Service, Beijing 100049, China;
    3. Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2018-04-02 Revised:2018-09-03 Online:2019-01-20 Published:2019-01-28
  • Supported by:
    National Natural Science Foundation of China (61300007,61305054); Foundation of the Key Lab of Software Development Environment (SKLSDE-2012ZX-28,SKLSDE-2014ZX-06)

摘要: 工业互联网是工业信息化进程中最受关注的热点,海量异构数据管理是其中的重点之一。传统的关系数据库(RDB)对海量多源异构数据的读写和检索都存在性能瓶颈,而近年来兴起的云数据管理方法主要是针对“键-值”(K-V)模式,无法依靠主键以外的数据属性对数据进行快速查找。提出了一种面向工业互联网的云存储方法——StoreCDB,在异构采样数据统一表达数据模型基础上,实现非结构化存储管理,同时,利用两级索引实现海量数据的快速检索。通过实验,在分布式集群实验平台上,采用海量高铁列车运行模拟数据,验证了StoreCDB具有良好的异构数据存储和检索性能,为工业互联网提供了一种新的数据管理方法。

关键词: 工业互联网, 异构数据, 海量数据管理, 分布式文件系统, 分级索引

Abstract: With the development of industrial informatization, industrial Internet has attracted many attentions, and massive heterogeneous data management is one of the most important issues. However, traditional relational database (RDB) limits the performance of access and retrieval of massive and heterogeneous data, while cloud data management mainly focuses on key-value (K-V) queries, which cannot quickly search data by using any data property other than the prime key. In this paper, a cloud storage framework-StoreCDB is proposed for data management in the industrial Internet. In StoreCDB, the heterogeneous data are represented by a uniform data model firstly and then stored in a distributed file and parallel architecture as unstructured data. In addition, a double-level index is proposed to support both key-value queries and RDB queries. This paper adopts a distributed cluster experimental platform and massive high-speed train operation simulation data to verify the framework. The experimental results show that StoreCDB has satisfactory heterogeneous data access and retrieval performance and provides a good solution for industrial Internet data management.

Key words: industrial Internet, heterogeneous data, massive data management, distributed file system, hierarchical index

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