Searching in Cloud Object Storage by Using a Metadata Model

被引:4
|
作者
Imran, Muhammad [1 ]
Hlavacs, Helmut [1 ]
机构
[1] Univ Vienna, Res Grp Entertainment Comp, Waehringer Str 29, A-1090 Vienna, Austria
关键词
D O I
10.1109/SKG.2013.28
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In a Cloud environment, an independent service or model referred to as object storage is used for the management of persistent data. This model provides a virtualized pool of storage resources and can be accessed via Application Programming Interface (API) and/or simply a browser. Object storage is used to store the persistent data from various users through put/get methods and it also store the virtual machine images as objects. Cloud storage services are used by enterprises, home users and researchers to store their files that vary in size and formats. With the huge amount of stored data which is mostly unstructured, comes the related issue of finding the exact data relevant to the requirements of a user. In current offerings such as Amazon, Eucalyptus and Google, the contents or objects are defined by a key-value pair. These objects can be listed based on the key, but searching and finding contents with any other parameters (metadata) such as type, size, owner, time stamps etc., is not supported. In this paper we propose a metadata model that address the issue of collecting, adding, and storing metadata associated with objects in Eucalyptus Cloud. Furthermore, the stored metadata is utilized to provide the feature of fast, effective and efficient searching of contents in a Cloud.
引用
收藏
页码:121 / 128
页数:8
相关论文
共 50 条
  • [1] Using object metadata to detect and tolerate attacks in Object Storage Devices
    Djemaiel, Yacine
    Boudriga, Noureddine
    [J]. GLOBECOM 2008 - 2008 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, 2008,
  • [2] Using provenance to efficiently improve metadata searching performance in storage systems
    Liu, Jinjun
    Feng, Dan
    Hua, Yu
    Peng, Bin
    Nie, Zhenhua
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2015, 50 : 99 - 110
  • [3] Metadata Caching Subsystem for Cloud Storage
    Niu Dejiao
    Cai Tao
    Zhan Yongzhao
    Ju Shiguang
    [J]. GREEN POWER, MATERIALS AND MANUFACTURING TECHNOLOGY AND APPLICATIONS II, 2012, 214 : 584 - 590
  • [4] xMeta: SSD-HDD-hybrid Optimization for Metadata Maintenance of Cloud-scale Object Storage
    Chen, Yan
    Ke, Qiwen
    Li, Huiba
    Wu, Yongwei
    Zhang, Yiming
    [J]. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, 2024, 21 (02)
  • [5] Phrase Searching for Encrypted Cloud Storage
    Gaware, Ankita J.
    Theng, Deepti. P.
    [J]. HELIX, 2018, 8 (05): : 3746 - 3749
  • [6] A formal model of learning object metadata
    Cardinaels, Kris
    Duval, Erik
    Olivie, Henk
    [J]. INNOVATIVE APPROACHES FOR LEARNING AND KNOWLEDGE SHARING, PROCEEDINGS, 2006, 4227 : 74 - 87
  • [7] Adaptive metadata load balancing for object storage systems
    [J]. Chen, T. (lovely696521@163.com), 2013, Chinese Academy of Sciences (24):
  • [8] Energy Efficient Metadata Management for Cloud Storage System
    Ko, Young Woong
    Kim, Sun-Jeong
    Kim, Jin
    Kim, Eui-Jik
    So, Jung Min
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2015,
  • [9] AIOps for a Cloud Object Storage Service
    Levin, Anna
    Garton, Shelly
    Kolodner, Elliot K.
    Lorenz, Dean H.
    Barabash, Katherine
    Kugler, Mike
    McShane, Niall
    [J]. 2019 IEEE INTERNATIONAL CONGRESS ON BIG DATA (IEEE BIGDATA CONGRESS 2019), 2019, : 165 - 169
  • [10] Study on Object-Storage system metadata load balancing
    Chen, Yongfeng
    Zhou, Dianyu
    [J]. COMPUTER AND INFORMATION TECHNOLOGY, 2014, 519-520 : 62 - 65