A Conceptual Framework for Intelligent Management of Workloads in Cloud Environment

Abstract

Cloud computing is an important paradigm for processing, computation, storage, and network bandwidth. Workloads are the amount of data given to the hardware resource for processing. Its behavior and properties play a major role in the efficient scheduling of requests to given resources. Also, it is very difficult to predict workloads nature if they are changing excessively. To address this issue, we propose a conceptual framework which can be used for efficient prediction and optimization of workloads in a cloud environment. Classification of optimization metrics based on the provider and consumer constraints are presented. In addition to this, some of the research gaps found during the study has been highlighted and also provided possible solutions in the cloud research domain. © 2020 IEEE.