MetaFa: Metadata Management Framework for Data Sharing in Data-Intensive Applications

被引：0
|
作者：
Ikebe, Minoru [1 ]
Inomata, Atsuo [1 ]
Fujikawa, Kazutoshi [1 ]
Sunahara, Hideki [1 ]
机构：
[1] Nara Inst Sci & Technol, Nara, Japan
来源：
DISTRIBUTED COMPUTING, ARTIFICIAL INTELLIGENCE, BIOINFORMATICS, SOFT COMPUTING, AND AMBIENT ASSISTED LIVING, PT II, PROCEEDINGS | 2009年 / 5518卷
关键词：
DataGrid; Data-Intensive Applications; Metadata; Data Management;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The data-intensive applications are naturally executed on the Internet and generate a huge amount of data. The generated data would be stored distributed storages. In such environments, a user cannot easily find the target: data by only filenames. The metadata, is very useful to represent the characteristics and semantics of data. If users can specify the metadata, they will access the target data intuitively. We have been developing a distributed data management system called "MetaFa". MetaFa can collect the metadata semi-automatically. In this paper, we discuss the implementation issues of MetaFa in order to collect metadata automatically.
引用
收藏
页码：655 / 658
页数：4
相关论文
共 50 条
  • [1] An automated C++ code and data partitioning framework for data management of data-intensive applications
    Milidonis, A
    Dimitroulakos, G
    Galanis, MD
    Theodoridis, G
    Goutis, C
    Catthoor, F
    [J]. SOFTWARE AND COMPILERS FOR EMBEDDED SYSTEMS, PROCEEDINGS, 2004, 3199 : 122 - 136
  • [2] A Framework for Data Partitioning for C++ Data-Intensive Applications
    A. Milidonis
    G. Dimitroulakos
    M. D. Galanis
    A. P. Kakarountas
    G. Theodoridis
    C. Goutis
    F. Catthoor
    [J]. Design Automation for Embedded Systems, 2004, 9 : 101 - 121
  • [3] A framework for the internationalization of data-intensive Web applications
    Belussi, A
    Posenato, R
    [J]. WEB ENGINEERING, PROCEEDINGS, 2004, 3140 : 478 - 482
  • [4] A framework for data partitioning for C++ data-intensive applications
    Milidonis, A
    Dimitroulakos, G
    Galanis, MD
    Kakarountas, AP
    Theodoridis, G
    Goutis, C
    Catthoor, F
    [J]. DESIGN AUTOMATION FOR EMBEDDED SYSTEMS, 2004, 9 (02) : 101 - 121
  • [5] Distributed Scientific Workflow Management for Data-Intensive Applications
    Shumilov, S.
    Leng, Y.
    El-Gayyar, M.
    Cremers, A. B.
    [J]. 12TH IEEE INTERNATIONAL WORKSHOP ON FUTURE TRENDS OF DISTRIBUTED COMPUTING SYSTEMS, PROCEEDINGS, 2008, : 65 - 73
  • [6] Applications in Data-Intensive Computing
    Shah, Anuj R.
    Adkins, Joshua N.
    Baxter, Douglas J.
    Cannon, William R.
    Chavarria-Miranda, Daniel G.
    Choudhury, Sutanay
    Gorton, Ian
    Gracio, Deborah K.
    Halter, Todd D.
    Jaitly, Navdeep D.
    Johnson, John R.
    Kouzes, Richard T.
    Macduff, Matthew C.
    Marquez, Andres
    Monroe, Matthew E.
    Oehmen, Christopher S.
    Pike, William A.
    Scherrer, Chad
    Villa, Oreste
    Webb-Robertson, Bobbie-Jo
    Whitney, Paul D.
    Zuljevic, Nino
    [J]. ADVANCES IN COMPUTERS, VOL 79, 2010, 79 : 1 - 70
  • [7] Metacomputing and data-intensive applications
    Messina, P
    [J]. WORLDWIDE COMPUTING AND ITS APPLICATIONS, 1997, 1274 : 226 - 236
  • [8] Distributed Data Access/Find System with Metadata for Data-Intensive Computing
    Ikebe, Minoru
    Inomata, Atsuo
    Fujikawa, Kazutoshi
    Sunahara, Hideki
    [J]. 2008 9TH IEEE/ACM INTERNATIONAL CONFERENCE ON GRID COMPUTING, 2008, : 361 - 366
  • [9] A Cost-Aware Management Framework for Placement of Data-Intensive Applications on Federated Cloud
    Moustafa Najm
    Rakesh Tripathi
    Mohammad Shadi Alhakeem
    Venkatesh Tamarapalli
    [J]. Journal of Network and Systems Management, 2021, 29
  • [10] Data replication techniques for data-intensive applications
    No, Jaechun
    Park, Chang Won
    Park, Sung Soon
    [J]. COMPUTATIONAL SCIENCE - ICCS 2006, PT 4, PROCEEDINGS, 2006, 3994 : 1063 - 1070
12345