Analysis_of_Remote_Sensing_Quantitative_Inversion_in_Cloud_Computing.ppt

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  • Analysis_of_Remote_Sensing_Quantitative_Inversion_in_Cloud_Computing.ppt

    1. 1. Analysis of Remote Sensing Quantitative Inversion in Cloud Computing Jing Dong , Yong Xue, Ziqiang Chen, Hui Xu, Yingjie Li Institute of Remote Sensing Applications Chinese Academy of Sciences July 29, 2011
    2. 2. <ul><li>Aerosol Optical Depth(AOD) Retrieval </li></ul><ul><li>High Performance Computing </li></ul>Institute of Remote Sensing Application, CAS
    3. 3. Outline <ul><li>An Introduction of Cloud Computing </li></ul><ul><li>Remote Sensing Quantitative Inversion & Cloud Computing </li></ul><ul><li>A Possible Cloud In Remote Sensing Quantitative Inversion </li></ul><ul><li>Discussion and Future Work </li></ul>1 Institute of Remote Sensing Application, CAS
    4. 4. Introduction <ul><li>What is Cloud Computing </li></ul><ul><li>What can Cloud Computing do </li></ul><ul><li>How does Cloud Computing work </li></ul>2 Institute of Remote Sensing Application, CAS
    5. 5. Introduction 3 <ul><li>SaaS </li></ul><ul><li>IaaS </li></ul><ul><li>PaaS </li></ul><ul><li>DaaS </li></ul>Software as a Service Infrastructure as a Service Platform as a Service Data as a Service Institute of Remote Sensing Application, CAS A large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet. —— Foster et al.(2008)
    6. 6. Introduction- cloud products <ul><li>Amazon Elastic Compute Cloud (Amazon EC2) of Amazon 、 Windows Azure of Microsoft 、 Google App Engine of Google 、 Blue Cloud of IBM </li></ul>4 Institute of Remote Sensing Application, CAS
    7. 7. Remote Sensing Quantitative Inversion & Cloud Computing <ul><li>Charge </li></ul><ul><li>eg. Amazon EC2 </li></ul><ul><li>Technical Support </li></ul><ul><li>eg. Google App Engine </li></ul><ul><li>Security </li></ul><ul><li>computing infrastructure maintained and controlled by third parties </li></ul>5 Institute of Remote Sensing Application, CAS
    8. 8. An example- Charge <ul><ul><li>Application—remote sensing quantitative inversion </li></ul></ul><ul><ul><li>Data Resource : MODIS for one year </li></ul></ul><ul><ul><ul><ul><li>Range : over China </li></ul></ul></ul></ul><ul><ul><ul><ul><li>total volume: 2.97TB (2008) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>per day: 8.4GB </li></ul></ul></ul></ul>6 Institute of Remote Sensing Application, CAS
    9. 9. Charge Standard of Amazon in US dollars-data transfer 7 Institute of Remote Sensing Application, CAS nearly 304.13 US dollars
    10. 10. An example- Charge <ul><ul><li>Data Resource : MODIS for one year </li></ul></ul><ul><ul><ul><ul><li>Range : over China </li></ul></ul></ul></ul><ul><ul><ul><ul><li>total volume: 2.97TB </li></ul></ul></ul></ul><ul><ul><ul><ul><li>per day: 8.4GB </li></ul></ul></ul></ul><ul><ul><li>processing time of geometric correction(GC) </li></ul></ul>8 Institute of Remote Sensing Application, CAS
    11. 11. Charge Standard of Amazon in US dollars 9 The price of on-demand instances Institute of Remote Sensing Application, CAS at least 832.2 US dollars
    12. 12. An example- Cost <ul><li>Data transfer in— nearly 304.13 US dollars for the whole year of 2008 </li></ul><ul><li>Instance rent for GC— at least 832.2 US dollars for one year data </li></ul><ul><li>The cost is so high </li></ul>10 Institute of Remote Sensing Application, CAS
    13. 13. An example - Technical Support <ul><li>Google App Engine </li></ul><ul><ul><li>Java </li></ul></ul><ul><ul><li>python </li></ul></ul><ul><li>most of the quantitative remote sensing inversion algorithms </li></ul><ul><ul><li>IDL </li></ul></ul><ul><ul><li>C++ </li></ul></ul>11 Institute of Remote Sensing Application, CAS
    14. 14. Security <ul><li>Data Security </li></ul><ul><li>Network connection </li></ul><ul><li>Emergency </li></ul><ul><ul><li>breakdown in 2008 and 2011 </li></ul></ul><ul><ul><li>service closed </li></ul></ul>12 Institute of Remote Sensing Application, CAS
    15. 15. A Possible Cloud 13 Advantage: avoid high cost for data transfer Disadvantage: not suitable for multi-source data comprehensive applications Institute of Remote Sensing Application, CAS
    16. 16. Discussions and Future Work <ul><li>Cloud computing would not necessarily suitable for all scientific applications, especially for geoscience </li></ul><ul><li>Standardized metadata management mechanism, more efficient data storage and sharing method, and more reliable security mechanism are needed </li></ul>Institute of Remote Sensing Application, CAS 14
    17. 17. Jing Dong Email: [email_address] URL: www.tgp.ac.cn

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