Dataffinic computing: Data-centric architecture to support digital trust

被引:0
|
作者
Tamura, Masahisa [1 ]
Yoshida, Eiji [1 ]
Yamada, Kohji [1 ]
机构
[1] Fujitsu Laboratories Ltd., Japan
来源
关键词
Distributed database systems - Digital storage - Trusted computing;
D O I
暂无
中图分类号
学科分类号
摘要
Recently, there is a movement gaining momentum to create business reforms and innovations by storing and utilizing large volumes of data generated on various sites. In addition to the structured data handled in conventional databases, advancements are being made in the use of video and other unstructured. There are three requirements for efficient utilization of unstructured data: data processing performance, cost-performance ratio, and data management. Fujitsu Laboratories is working on the R&D of Dataffinic Computing, which uses distributed storage systems to achieve high-speed processing of large volumes of data, as a data-centric architecture that supports the utilization of massive volumes of data. This paper outlines data neighborhood processing technology, large-volume memory technology, and high-speed thin client technology, which are elemental technologies of Dataffinic Computing. It also presents an approach to video monitoring systems as an application example. © 2020 Fujitsu Ltd. All rights reserved.
引用
收藏
页码:67 / 71
相关论文
共 50 条
  • [1] Dataffinic Computing: Data-Centric Architecture to Support Digital Trust
    Tamura, Masa Hisa
    Yoshida, Eiji
    Yamada, Kohji
    [J]. FUJITSU SCIENTIFIC & TECHNICAL JOURNAL, 2020, 56 (01): : 67 - 71
  • [2] SOLROS: A Data-Centric Operating System Architecture for Heterogeneous Computing
    Min, Changwoo
    Kang, Woonhak
    Kumar, Mohan
    Kashyap, Sanidhya
    Maass, Steffen
    Jo, Heeseung
    Kim, Taesoo
    [J]. EUROSYS '18: PROCEEDINGS OF THE THIRTEENTH EUROSYS CONFERENCE, 2018,
  • [3] Data-Centric Intelligent Computing
    Jun Shen
    Chih-Cheng Hung
    Ghassan Beydoun
    Yan Li
    William Guo
    [J]. International Journal of Computational Intelligence Systems, 2018, 11 : 616 - 617
  • [4] Data-Centric Intelligent Computing
    Shen, Jun
    Hung, Chih-Cheng
    Beydoun, Ghassan
    Li, Yan
    Guo, William
    [J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2018, 11 (01) : 616 - 617
  • [5] Data-centric decision support
    Kulhavy, R
    [J]. PROCEEDINGS OF THE 2002 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2002, 1-6 : 3395 - 3400
  • [6] An Incrementally Deployable Network Architecture to Support Both Data-Centric and Host-Centric Services
    Luo, Hongbin
    Zhang, Hongke
    Zukerman, Moshe
    Qiao, Chunming
    [J]. IEEE NETWORK, 2014, 28 (04): : 58 - 65
  • [7] Data Subsetting: A Data-Centric Approach to Approximate Computing
    Kim, Younghoon
    Venkataramani, Swagath
    Chandrachoodan, Nitin
    Raghunathan, Anand
    [J]. 2019 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE), 2019, : 576 - 581
  • [8] DBGlobe: A data-centric approach to global computing
    Karakasidis, A
    Pitoura, E
    [J]. 22ND INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS WORKSHOP, PROCEEDINGS, 2002, : 735 - 740
  • [9] Memory for Data-Centric Computing: A Technology Perspective
    Wang, Yih
    [J]. 2020 INTERNATIONAL SYMPOSIUM ON VLSI DESIGN, AUTOMATION AND TEST (VLSI-DAT), 2020,
  • [10] Quantum computing for data-centric engineering and science
    Herbert, Steven
    [J]. DATA-CENTRIC ENGINEERING, 2022, 3 (04):