Semantic resource classification using statistical analysis for application characteristics in intercloud environment

Abstract

Scientists gain benefits from scalable resource provisioning on-demand, and various computing environments by using cloud computing resources for their applications. However, many cloud computing providers offer their cloud resources according to their own rules. The descriptions of various cloud resources also differ for each vendor. Subsequently, it becomes difficult to find suitable cloud resources given the characteristics of an application. Scientists therefore, select resources used in previous experiments or best performance resources without considering the characteristics of their applications. There is the need to standardize notations to support simple selection of cloud resources without the constraints of providers. Intercloud can use cloud resources without considering cloud providers in hybrid cloud environments. Intercloud project has been studied for interoperability and creates mOSAIC ontology to conceptualize various resources. However, the mOSAIC ontology attributes are limited when considering characteristics of an application. We propose a semantic engine to provide semantic cloud resource services in intercloud environment. We define a rule of categorized resource description with reference to mOSAIC ontology attributes which includes added factors needed to represent application characteristics. We also develop a semantic engine which can choose semantically similar cloud resources using statistical analysis while considering the characteristics of an application. The semantic engine can also classify resources dynamically according to application specifications.