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遥感云计算:研究现状与展望 被引量:9

Remote Sensing Cloud Computing:Current Research and Prospect
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摘要 随着遥感技术和计算机技术的迅猛发展,遥感数据在深度、广度和密度3个层次上不断汇聚和交叉融合,进而导致了遥感大数据概念的诞生。作为高性能计算最具代表性的云计算技术可以有效地处理大数据。首先引入了遥感大数据和遥感云计算的概念,其次对目前遥感云计算的3个研究热点:遥感大数据的存储、遥感云计算数据处理和遥感云计算任务调度进行了综述,最后对遥感云计算未来的发展趋势进行了展望。 With repaid development of remote sensing and computer technologies,remote sensing data continuously converge,intersect and integrate in the dimensions of depth,width and density.All these lead to the birth of remote sensing big data concept.As a classical technology in big data era,cloud computing is effective for handling big data.First of all,this paper introduces the concept of remote sensing big data and remote sensing cloud computing.Secondly,it gives review on three research highlights:remote sensing big data storage,remote sensing data processing and remote sensing cloud computing task scheduling.In the end,the paper forecasts the future of remote sensing cloud computing.
出处 《装备学院学报》 2015年第5期95-100,共6页 Journal of Equipment Academy
基金 部委级资助项目
关键词 遥感云计算 遥感大数据 云计算数据处理 云计算任务调度 remote sensing cloud computing remote sensing big data cloud computing data processing cloud computing task scheduling
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  • 1李德仁,邵振峰.论新地理信息时代[J].中国科学(F辑:信息科学),2009,39(6):579-587. 被引量:106
  • 2GONG JianYa,XIANG LongGang,CHEN Jing & YUE Peng State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430072,China.Multi-source geospatial information integration and sharing in Virtual Globes[J].Science China(Technological Sciences),2010,53(S1):1-6. 被引量:10
  • 3GUO Wei,GONG JianYa,JIANG WanShou,LIU Yi & SHE Bing State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430074,China.OpenRS-Cloud:A remote sensing image processing platform based on cloud computing environment[J].Science China(Technological Sciences),2010,53(S1):221-230. 被引量:24
  • 4Chen K, Zheng WM. Cloud computing: System instances and current research. Journal of Software, 2009,20(5):1337-1348 (in Chinese with English abstract), http://www.jos.org.cn/1000-9825/3493.htm [doi: 10.3724/SP.J.1001.2009.03493].
  • 5Dash D, Kantere V, Ailamaki A. An economic model for self-tuned cloud caching. In: Ioannidis YE, Lee DL, Ng RT, eds. Proc. of the 25th Int'l Conf. on Data Engineering (ICDE 2009). New York: IEEE Computer Society Press, 2009. 1687-1693. [dol: 10.1109/ ICDE.2009.143 ].
  • 6Feng DG, Zhang M, Zhang Y, Xu Z. Study on cloud computing security. Journal of Software, 2011,22(1):71-83 (in Chinese with English abstract), http://www.jos.org.cn/1000-9825/3958.htm [doi: 10.3724/SP.J.1001.2011.03958].
  • 7Xu M, Gao D, Deng C, Luo ZG, Sun SL. Cloud computing boosts business intelligence of telecommunication industry. In: Jaatun MG, Zhao GS, Rong CM, eds. Proc. of the 1st Int'l Conf. on Cloud Computing (CloudCom 2009). Berlin: Springer-Verlag, 2009. 224-231. [doi: 10.1007/978-3-642-10665-1_20].
  • 8Qi J, Qian L, Luo ZG. Distributed structured database system HugeTable. In: Jaatun MG, Zhao GS, Rong CM, eds. Proc. of the 1st Int'l Conf. on Cloud Computing (CloudCom 2009). Berlin: Springer-Verlag, 2009. 338-346. [doi: 10.1007/978-3-642-10665- 1_31].
  • 9Abouzeid A, Bajda-Pawlikowski K, Abadi DJ, Silberschatz A, Rasin A. HadoopDB: An architectural hybrid of MapReduce and DBMS technologies for analytical workloads. PVLDB, 2009,2(1):922-933.
  • 10Ahrens M, Alonso G. Relational databases, virtualization, and the cloud. In: Abiteboul S, B6hrn K, Koch C, Tan KL, eds. Proc. of the 27th Int'l Conf. on Data Engineering (ICDE 2011). New York: IEEE Computer Society Press, 2011. 1254. [doi: 10.1109/ICDE. 2011.5767966].

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