An integrated architectural framework for geoprocessing in cloud environment

Spatial data infrastructure had ensured the availability of geospatial data over the local and global boundaries to be used in more flexible and efficient manner. With the enhancement in web service technologies the need of geoprocessing the geospatial data from various heterogeneous sources over the web, to produce valuable information is of great interest among research community. Towards this implementation of geoprocessing web, open geospatial consortium (OGC) has provided several web processing service standards for handling the geoprocess over the web. Most of the current existing geoprocessing web platforms inherit the capabilities of these web processing service standards and protocols define by OGC. However there exist several challenges that includes, growing intensity of data, high performance computing, real time data processing, and to provide robust, reliable, and cost effective geoprocess services to the end user. The future of geo-processing lies in the adoption of cloud computing to overcome the existing challenges. Characteristics of cloud computing including scalability, elasticity, pay-per-use, and self provisioning, offers a more reliable, on demand, and cost effective geoprocessing services to its end user. In this context the study makes an attempt to analyze the current state of geoprocessing services over cloud, with exiting GIS Cloud platform solutions in the literature to counter the challenges of GIS cloud. Furthermore, study proposes a design and architectural framework for geoprocessing over Cloud platform, based on OGC standards. The architecture includes developing geoprocessing service, and data management services as an essential part while storing/processing the geospatial data from heterogeneous sources. The architecture model including data management and geoprocessing can be bind together in a cloud platform to have an on demand service as per the requirement of end user.