Distributed computing model for processing remotely sensed images based on grid computing
Shen Z. F. ; Luo J. C. ; Huang G. G. ; Ming D. P. ; Ma W. F. ; Sheng H.
2007
关键词grid computing middleware Web services remotely sensed image processing distributed and parallel processing computing model design system environments algorithms discovery network gis
英文摘要With advances in remote-sensing technology, the large volumes of data cannot be analyzed efficiently and rapidly, especially with arrival of high-resolution images. The development of image-processing technology is an urgent and complex problem for computer and geo-science experts. It involves, not only knowledge of remote sensing, but also of computing and networking. Remotely sensed images need to be processed rapidly and effectively in a distributed and parallel processing environment. Grid computing is a new form of distributed computing, providing an advanced computing and sharing model to solve large and computationally intensive problems. According to the basic principle of grid computing, we construct a distributed processing system for processing remotely sensed images. This paper focuses on the implementation of such a distributed computing and processing model based on the theory of grid computing. Firstly, problems in the field of remotely sensed image processing are analyzed. Then, the distributed (and parallel) computing model design, based on grid computing, is applied. Finally, implementation methods with middleware technology are discussed in detail. From a test analysis of our system, TARIES.NET, the whole image-processing system is evaluated, and the results show the feasibility of the model design and the efficiency of the remotely sensed image distributed and parallel processing system. (C) 2006 Elsevier Inc. All rights reserved.
出处Information Sciences
177
2
504-518
收录类别SCI
语种英语
ISSN号0020-0255
内容类型SCI/SSCI论文
源URL[http://ir.igsnrr.ac.cn/handle/311030/23102]  
专题地理科学与资源研究所_历年回溯文献
推荐引用方式
GB/T 7714
Shen Z. F.,Luo J. C.,Huang G. G.,et al. Distributed computing model for processing remotely sensed images based on grid computing. 2007.
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