Fog Computing Architecture for Scalable Processing of Geospatial Big Data

IF 0.4 Q4 GEOGRAPHY International Journal of Applied Geospatial Research Pub Date : 1900-01-01 DOI:10.4018/ijagr.2020010101

Rabindra Kumar Barik, R. Priyadarshini, R. K. Lenka, Harishchandra Dubey, K. Mankodiya

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引用次数: 6

Abstract

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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地理空间大数据可扩展处理的雾计算架构

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

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International Journal of Applied Geospatial Research GEOGRAPHY-

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1.20

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0.00%

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