FogGIS: Fog Computing for geospatial big data analytics

Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog Computing based framework named FogGIS for mining analytics from geospatial data. It has been built a prototype using Intel Edison, an embedded microprocessor. FogGIS has validated by doing preliminary analysis including compression and overlay analysis. Results showed that Fog Computing hold a great promise for analysis of geospatial data. Several open source compression techniques have been used for reducing the transmission to the cloud.