Add to ORKGAbstract-As the deep development of spatial information sharing service, it brings forward high request to usability and expansibility of supporting system. Based on large-scale scalable server cluster, cloud computing brings hopes to resolves the existing difficult problems in the domain of geospatial information service. In this paper, we imported cloud computing technology including MapReduce model and Hadoop platform into the domain of geographic information system (GIS). Those key technology problems in the application of GIS such as spatial data storage, spatial index and spatial operation were described and studied in detail. We evaluated the performance and efficiency of spatial operation in Hadoop experiment environment with the re...
University of Minnesota Ph.D. dissertation. June 2016. Major: Computer Science. Advisor: Mohamed Mok...
Recent development in both hardware and software infrastructure have given big push and new directio...
Geospatial data is getting bigger and such large and complex datasets are becoming more and more dif...
Abstract — Cloud computing can be used to generate the 3D noise maps in ubiquitous cities. Here in t...
Cloud computing is one of the main issues of interest to the scientific community of the spatial dat...
Cloud Computing is an approach that provides computation and storage services on-demand to clients o...
Abstract—In this work, we leverage Cloud computing tech-nologies in scaling out data management in g...
With the development of spatial information industry, traditional systems that are limited by scalab...
The emergence of new tools and technologies to gather the information generate the problem of proces...
Abstract—Data volumes of GPS recorded locations and many other types of geospatial data are fast inc...
Abstract—Cloud computing provides a way of determining dynamically scalable and virtualized resource...
Support of high performance queries on large volumes of spatial data becomes increasingly important ...
AbstractIn this paper, we investigate the potential of cloud computing for data-intensive spatial in...
In this paper we are going to discuss HadoopBased data management Service For Cloud. Data security i...
Cloud computing has emerged as a leading computing paradigm, with an increasing number of geographic...
University of Minnesota Ph.D. dissertation. June 2016. Major: Computer Science. Advisor: Mohamed Mok...
Recent development in both hardware and software infrastructure have given big push and new directio...
Geospatial data is getting bigger and such large and complex datasets are becoming more and more dif...
Abstract — Cloud computing can be used to generate the 3D noise maps in ubiquitous cities. Here in t...
Cloud computing is one of the main issues of interest to the scientific community of the spatial dat...
Cloud Computing is an approach that provides computation and storage services on-demand to clients o...
Abstract—In this work, we leverage Cloud computing tech-nologies in scaling out data management in g...
With the development of spatial information industry, traditional systems that are limited by scalab...
The emergence of new tools and technologies to gather the information generate the problem of proces...
Abstract—Data volumes of GPS recorded locations and many other types of geospatial data are fast inc...
Abstract—Cloud computing provides a way of determining dynamically scalable and virtualized resource...
Support of high performance queries on large volumes of spatial data becomes increasingly important ...
AbstractIn this paper, we investigate the potential of cloud computing for data-intensive spatial in...
In this paper we are going to discuss HadoopBased data management Service For Cloud. Data security i...
Cloud computing has emerged as a leading computing paradigm, with an increasing number of geographic...
University of Minnesota Ph.D. dissertation. June 2016. Major: Computer Science. Advisor: Mohamed Mok...
Recent development in both hardware and software infrastructure have given big push and new directio...
Geospatial data is getting bigger and such large and complex datasets are becoming more and more dif...