• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (08): 1447-1454.

• 论文 • 上一篇    下一篇

云计算环境中高效可扩展的元数据管理方法

黄斌1,2,彭宇行3   

  1. (1.贵州师范大学数学与计算机科学学院,贵州 贵阳 550001;2.武汉大学计算机学院,湖北 武汉 430072;3.国防科学技术大学计算机学院,湖南 长沙 410073)
  • 收稿日期:2013-12-12 修回日期:2014-04-03 出版日期:2014-08-25 发布日期:2014-08-25
  • 基金资助:

    国家973 计划资助项目(2011CB302601);国家863计划资助项目(2011AA01A202);湖南省科技计划资助项目(2013FJ4335,2013FJ4295)

An efficient scalable metadata
management method in cloud computing           

HUANG Bin1,2,PENG Yuxing3   

  1. (1.School of Mathematics and Computer Science,Guizhou Normal University,Guiyang 550001;
    2.School of Computer,Wuhan University,Wuhan 430072;
    3.College of Computer,National University of Defense Technology,Changsha 410073,China)
  • Received:2013-12-12 Revised:2014-04-03 Online:2014-08-25 Published:2014-08-25

摘要:

针对现有可扩展的元数据管理方法存在性能较低问题,提出一种高效可扩展的元数据管理方法,它首先采用动态二叉映射树来实现元数据服务器精确定位,然后采用延迟更新方法来动态更新二叉映射树,最后提出动态K叉编码树的元数据组织方法以提高元数据服务器扩展时选择迁移元数据的速度。实验结果表明,它有效提高了云计算环境中可扩展元数据管理方法的效率。

关键词: 云计算, 元数据, 高效, 可扩展

Abstract:

Aiming at the lower performance problem of the existing metadata management methods in cloud computing,an efficient scalable metadata management method is proposed in cloud computing.Firstly,a dynamic binary mapping tree is used to achieve the precise positioning of the metadata server.Secondly,a lazy update technique is adopted to dynamically update the binary mapping tree.Finally,a dynamic K tree is proposed to improve the speed of selecting migrated metadata during MDS splitting.The experimental results show that the method can effectively improve the efficiency of the scalable metadata management method in cloud computing.

Key words: cloud computing;metadata;efficient;scalable