A scalable Cloud-based system for data-intensive spatial analysis

被引:0
作者
R. O. Sinnott
W. Voorsluys
机构
[1] University of Melbourne,Department of Computing and Information Systems
来源
International Journal on Software Tools for Technology Transfer | 2016年 / 18卷
关键词
e-Infrastructure; Urban research; Cloud computing ; Geospatial systems; Spatial analysis;
D O I
暂无
中图分类号
学科分类号
摘要
Advances in Cloud computing technology and the availability of affordable and easy to use Cloud services are enabling a multitude of scientific applications to use these resources as primary or secondary computing infrastructure. The urban and built environment research domain is one area that can benefit greatly from Cloud computing. The global population growth and increase in the size and population of cities raise many challenges for governments, planners and researchers alike. The Australian Urban Research Infrastructure Network (AURIN—http://www.aurin.org.au) project has been tasked with developing an advanced platform (e-Infrastructure) across Australia to tackle these challenges. The platform leverages large-scale Cloud resources to provide federated data access to, at present over 1100 data sets from major and often definitive government and industry data-rich organisations, and for scalable data processing and visualisation. The original AURIN tools were developed using the object modelling system (OMS) and supported integrated workflows to define and enact/re-enact scientific processes. More recently the work has evolved to focus more on delivery of a workbench offering a rich range of tools delivered through an extensible workflow environment. In this paper, we provide the background to AURIN including the scientific drivers that are shaping the work and the realisation of the Cloud-based AURIN environment. We focus in particular on the workflow environment and show how it seamlessly utilizes the Cloud for urban research processes focused especially on data-intensive spatial analysis. We illustrate the utilisation of this workflow environment across a range of case studies reflecting urban research activities.
引用
收藏
页码:587 / 605
页数:18
相关论文
共 50 条
  • [41] Cloud-based scalable object detection and classification in video streams
    Yaseen, Muhammad Usman
    Anjum, Ashiq
    Rana, Omer
    Hill, Richard
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 80 : 286 - 298
  • [42] Cloud-Based Data Architecture Security
    N. A. Semenov
    A. A. Poltavtsev
    Automatic Control and Computer Sciences, 2019, 53 : 1056 - 1064
  • [43] Cloud-based NoSQL Data Migration
    Bansel, Aryan
    Gonzalez-Velez, Horacio
    Chis, Adriana E.
    2016 24TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, AND NETWORK-BASED PROCESSING (PDP), 2016, : 224 - 231
  • [44] A Scalable Cloud-Based Android App Repackaging Detection Framework
    Li, Jinghua
    Liu, Xiaoyan
    Zhang, Huixiang
    Mu, Dejun
    GREEN, PERVASIVE, AND CLOUD COMPUTING, 2016, 9663 : 113 - 125
  • [45] Cloud-based Personal Data Protection System and Its Performance Evaluation
    Liu, Jung-Chun
    Lin, Chu-Hsing
    Lee, Ken-Yu
    JOURNAL OF INTERNET TECHNOLOGY, 2019, 20 (06): : 1721 - 1727
  • [46] WaaS: Workflow-as-a-Service for the Cloud with Scheduling of Continuous and Data-Intensive Workflows
    Esteves, Sergio
    Veiga, Luis
    COMPUTER JOURNAL, 2016, 59 (03) : 371 - 383
  • [47] Design and Evaluation of Cloud-Based Students Data Management System Usability
    Al-Sumaty, Rami Muqbel
    Umar, Irfan Naufal
    2018 INTERNATIONAL CONFERENCE ON SMART COMPUTING AND ELECTRONIC ENTERPRISE (ICSCEE), 2018,
  • [48] Benchmarking Cloud-based SCADA System
    Yi, Mao
    Mueller, Harald
    Yu, Liu
    Chuan, Jiang
    2017 9TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 2017, : 122 - 129
  • [49] A Cloud-based Signage Network System
    Peng, Yan
    2013 FOURTH INTERNATIONAL CONFERENCE ON DIGITAL MANUFACTURING AND AUTOMATION (ICDMA), 2013, : 17 - 20
  • [50] Deadline based scheduling for data-intensive applications in clouds
    Fu Xiong
    Cang Yeliang
    Zhu Lipeng
    Hu Bin
    Deng Song
    Wang Dong
    The Journal of China Universities of Posts and Telecommunications, 2016, (06) : 8 - 15