Cloud enabled SDI architecture: a review

被引:14
|
作者
Tripathi, Ashutosh Kumar [1 ]
Agrawal, Sonam [1 ]
Gupta, R. D. [1 ,2 ]
机构
[1] Motilal Nehru Natl Inst Technol Allahabad, GIS Cell, Prayagraj 211004, Uttar Pradesh, India
[2] Motilal Nehru Natl Inst Technol Allahabad, Civil Engn Dept, Prayagraj 211004, Uttar Pradesh, India
关键词
Spatial data infrastructure (SDI); National Spatial Data Infrastructure (NSDI); Cloud computing; Geographic information system (GIS); Service oriented architecture (SOA); SPATIAL DATA INFRASTRUCTURE; KNOWLEDGE GENERATION; DECISION-MAKING; DIGITAL EARTH; BIG DATA; MANAGEMENT; SERVICE; CYBERINFRASTRUCTURE; CHALLENGES; INSPIRE;
D O I
10.1007/s12145-020-00446-9
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
With the advancement of GIS technology since its inception in 1960's, many educational institutions, government departments, public/ private sectors and individuals have started its use for the production and management of spatial data. Spatial Data Infrastructure (SDI) concept was introduced in the early1990's and provides a set of technologies, standards, protocols, policies and guidelines on the whole cycle of geospatial data production and distributions, i.e., from data capture to storage and to sharing. SDI initiative at national level, termed as National Spatial Data Infrastructure (NSDI), has been taken by different countries including India. Geospatial community is facing various challenges like handling of large volumes of geospatial data, requirement of high computing resources to process geospatial data, scalability and interoperability. Therefore, need of advanced technologies in the form of SDI and cloud computing is realized to resolve the above challenges. Cloud computing has several characteristics like scalability, elasticity and self-provisioning that offers high-performance computing resources to perform geoprocessing efficiently. The main aim of the present paper is to study SDI and its components along with analysis and comparison of NSDI of various countries as well as to conceptualize and discuss service oriented architecture of cloud enabled SDI. Several challenges of the spatial data handling and processing that occurred due to the high intensity of data and lack of processing capability can be solved by adopting proposed cloud enabled SDI architecture. This research will help geospatial community and SDI developers in various perspectives including data sharing and management, interoperability, security and reliability, fault tolerance, mass market solution, upfront cost and global collaboration.
引用
收藏
页码:211 / 231
页数:21
相关论文
共 50 条
  • [1] Cloud enabled SDI architecture: a review
    Ashutosh Kumar Tripathi
    Sonam Agrawal
    R. D. Gupta
    Earth Science Informatics, 2020, 13 : 211 - 231
  • [2] GeoCloud4SDI: a cloud enabled open framework for development of spatial data infrastructure at city level
    Tripathi, Ashutosh Kumar
    Agrawal, Sonam
    Gupta, Rajan Dev
    EARTH SCIENCE INFORMATICS, 2023, 16 (01) : 481 - 500
  • [3] The Cloud-Enabled Architecture of the Clinical Data Repository in Poland
    Augustyn, Dariusz R.
    Wycislik, Lukasz
    Sojka, Mateusz
    SUSTAINABILITY, 2021, 13 (24)
  • [4] GeoCloud4SDI: a cloud enabled open framework for development of spatial data infrastructure at city level
    Ashutosh Kumar Tripathi
    Sonam Agrawal
    Rajan Dev Gupta
    Earth Science Informatics, 2023, 16 : 481 - 500
  • [5] Survey on Cloud Robotics Architecture and Model-Driven Reference Architecture for Decentralized Multicloud Heterogeneous-Robotics Platform
    Siriweera, Akila
    Naruse, Keitaro
    IEEE ACCESS, 2021, 9 : 40521 - 40539
  • [6] A CLOUD-ENABLED GEOSPATIAL BIG DATA PLATFORM FOR DISASTER INFORMATION SERVICES
    He, Lianlian
    Yue, Peng
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 5658 - 5661
  • [7] A Comprehensive Cloud Architecture for Machine Learning-enabled Research
    Stubbs, Joe
    Freeman, Nathan
    Indrakusuma, Dhanny
    Garcia, Christian
    Halbach, Francois
    Hammock, Cody
    Curbelo, Gilbert
    Jamthe, Anagha
    Packard, Mike
    Fields, Alex
    PRACTICE AND EXPERIENCE IN ADVANCED RESEARCH COMPUTING 2024, PEARC 2024, 2024,
  • [8] A REVIEW ON SOFTWARE-DEFINED NETWORKING ENABLED IOT CLOUD COMPUTING
    Badotra, Sumit
    Panda, Surya Narayan
    IIUM ENGINEERING JOURNAL, 2019, 20 (02): : 105 - 126
  • [9] Intelligent architecture and platforms for private edge cloud systems: A review
    Xu, Xiyuan
    Zang, Shaobo
    Bilal, Muhammad
    Xu, Xiaolong
    Dou, Wanchun
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2024, 160 : 457 - 471
  • [10] Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review
    Ali, Omar
    Shrestha, Anup
    Soar, Jeffrey
    Wamba, Samuel Fosso
    INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2018, 43 : 146 - 158