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-based framework named Fog GIS for mining analytics from geospatial data. We built a prototype using Intel Edison, an embedded microprocessor. We validated the FogGIS by doing preliminary analysis. including compression, and overlay analysis. Results showed that Fog computing hold a great promise for analysis of geospatial data. We used several open source compression techniques for reducing the transmission to the cloud.
@article{arxiv.1701.02601,
title = {FogGIS: Fog Computing for Geospatial Big Data Analytics},
author = {Rabindra K. Barik and Harishchandra Dubey and Arun B. Samaddar and Rajan D. Gupta and Prakash K. Ray},
journal= {arXiv preprint arXiv:1701.02601},
year = {2017}
}
Comments
6 pages, 4 figures, 1 table, 3rd IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (09-11 December, 2016) Indian Institute of Technology (Banaras Hindu University) Varanasi, India