Semantic Enabled Cloud for Meteorological Data Processing Applications

Abstract

Meteorological data is being captured regularly by satellites. It can be utilized in multiple ways to obtain useful predictions and meaningful information. This domain contains many applications which involves huge amount of image processing which are extremely compute intensive. To process and execute this type of high computational tasks,enormous amount of resources is needed. For such scenario, Cloud Computing is a better and smart approach for executing this tasks. As current Cloud Service Providers (CSP's) deliver resources in optimal way by using various scheduling techniques but also with manual intervention for selecting required resources, which degrades the resource usage performance. An approach is proposed to deploy this compute intensive tasks over Cloud, but with intelligent decision making capability as managing the resources productively over the Cloud is challenging. This type of cloud which is proposed with advanced and smart decision making ability is called 'Semantic Cloud' which manages the semantic allocation of resources for adaptive formation of virtual machines(VM's) to deploy applications, as the automation has been needed for making cloud resources utilization potent.