Hybrid Cloud framework for Object Storage based Geo Spatial Remote Sensing Data Processing

With the increase in the collection and usage of the geo spatial data by several application developers and users, the demand to deliver the geospatial data and the application processing is growing day by day. The data collected from several geo spatial sensors needs to be stored, processed and analysed to extract the value out of the data. Since the geospatial data volumes are increasing, hence there is a need to explore the better storage mechanisms and the automated processing mechanisms for the application and data delivery to the end users. In this work, we design a Hybrid Cloud computing framework for organizing the Geospatial data over Object based storages for the data preserving and a platform to quickly build and publish the geospatial services as cloud based services. This framework allows accessing the geospatial data even from public cloud storages. For processing the public cloud data, the data to be retrieved at local machine and processed by the services running on private cloud environment. The services are executed over a large scale distributed virtual machines provisioned by the underlying cloud infrastructure.