地理空间大数据可扩展处理的雾计算架构

IF 0.4 Q4 GEOGRAPHY
Rabindra Kumar Barik, R. Priyadarshini, R. K. Lenka, Harishchandra Dubey, K. Mankodiya
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引用次数: 6

摘要

Geospatialdataanalysisusingcloudcomputingplatformisoneofthepromisingareasforanalysing,检索,andprocessingvolumetricdata。Fogcomputingparadigmassistscloudplatformwherefog devicestrytoincreasethethroughputandreducelatencyattheedgeoftheclient。Inthisresearchpaper, theauthorsdiscusstwocasestudiesongeospatialdataanalysisusingFog-assistedcloudcomputing即:(1)GangaRiverBasinManagementSystem;and(2)TourismInformationManagementof印度。BothcasestudiesevaluateproposedGeoFogarchitectureforefficientanalysisandmanagement ofgeospatial bigdata采用雾计算。The authorsdevelopedaprototypeofGeoFog architectureusingIntelEdisonandRaspberryPidevices。Theauthors implementedsomeof theopensourcecompressionmethodsforreducingthedatatransmissionoverloadinthecloud。Proposed architectureperformsdatacompressionandoverlayanalysisofdata。Theauthorsfurtherdiscussed theimprovementinscalabilityandtimeanalysisusingproposedGeoFogarchitectureandGeospark工具。Discussedresultsshowthemeritoffogcomputingthatholdsanenormouspromiseforenhanced analysisofgeospatialbigdatainriverGangabasinandtourisminformationmanagementscenario。关键词云计算,地理空间大数据,地理空间数据,K-Means,开源GIS,叠加分析,河流,旅游,可视化
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fog Computing Architecture for Scalable Processing of Geospatial Big Data
Geospatialdataanalysisusingcloudcomputingplatformisoneofthepromisingareasforanalysing, retrieving,andprocessingvolumetricdata.Fogcomputingparadigmassistscloudplatformwherefog devicestrytoincreasethethroughputandreducelatencyattheedgeoftheclient.Inthisresearchpaper, theauthorsdiscusstwocasestudiesongeospatialdataanalysisusingFog-assistedcloudcomputing namely,(1)GangaRiverBasinManagementSystem;and(2)TourismInformationManagementof India.BothcasestudiesevaluateproposedGeoFogarchitectureforefficientanalysisandmanagement ofgeospatial bigdata employing fog computing.The authorsdevelopedaprototypeofGeoFog architectureusingIntelEdisonandRaspberryPidevices.Theauthors implementedsomeof the opensourcecompressionmethodsforreducingthedatatransmissionoverloadinthecloud.Proposed architectureperformsdatacompressionandoverlayanalysisofdata.Theauthorsfurtherdiscussed theimprovementinscalabilityandtimeanalysisusingproposedGeoFogarchitectureandGeospark tool.Discussedresultsshowthemeritoffogcomputingthatholdsanenormouspromiseforenhanced analysisofgeospatialbigdatainriverGangabasinandtourisminformationmanagementscenario. KeywoRDS Cloud Computing, Geospatial Big Data, Geospatial Data, K-Means, Open Source GIS, Overlay Analysis, River, Tourism, Visualization
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来源期刊
CiteScore
1.20
自引率
0.00%
发文量
22
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