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Fog Computing Architecture for Scalable Processing of Geospatial Big Data

Fog Computing Architecture for Scalable Processing of Geospatial Big Data
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Author(s): Rabindra K. Barik (School of Computer Applications, Kalinga Institute of Industrial Technology, Bhubaneswar, India), Rojalina Priyadarshini (C.V. Raman College of Engineering, Bhubaneswar, India), Rakesh K. Lenka (IIIT-Bhubaneswar, Bhubaneswar, India), Harishchandra Dubey (University of Texas, Dallas, USA) and Kunal Mankodiya (University of Rhode Island, Kingston, USA)
Copyright: 2020
Volume: 11
Issue: 1
Pages: 20
Source title: International Journal of Applied Geospatial Research (IJAGR)
Editor(s)-in-Chief: Donald Patrick Albert (Sam Houston State University, USA) and Samuel Adu-Prah (Sam Houston State University, USA)
DOI: 10.4018/IJAGR.2020010101


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Geospatial data analysis using cloud computing platform is one of the promising areas for analysing, retrieving, and processing volumetric data. Fog computing paradigm assists cloud platform where fog devices try to increase the throughput and reduce latency at the edge of the client. In this research paper, the authors discuss two case studies on geospatial data analysis using Fog-assisted cloud computing namely, (1)Ganga River Basin Management System; and (2)Tourism Information Management of India. Both case studies evaluate proposed GeoFog architecture for efficient analysis and management of geospatial big data employing fog computing. The authors developed a prototype of GeoFog architecture using Intel Edison and Raspberry Pi devices. The authors implemented some of the open source compression methods for reducing the data transmission overload in the cloud. Proposed architecture performs data compression and overlay analysis of data. The authors further discussed the improvement in scalability and time analysis using proposed GeoFog architecture and Geospark tool. Discussed results show the merit of fog computing that holds an enormous promise for enhanced analysis of geospatial big data in river Ganga basin and tourism information management scenario.

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