Optimization of QoS parameters through flexible Resource Scheduling in Finite Population Cloud Environment

Abstract

Cloud computing renders more ability to existing internet technologies and web cluster to fit the emerging business needs by accessing distributed computing resources. It supports processing large data utilizing clusters of commodity computers to control the next generation data centers and empowered application service providers for deploying applications depending on user Quality of Service (QoS) requirements. This would demand tools and mechanisms for analyzing the performance of the cloud system. In this paper, we present two scheduling policies along with an analytical resource prediction model for each policy for private cloud system. Queuing models are employed to provide exact performance measures of such systems. Various performance measures under various load, network time- delay and buffer size of both the systems indicate that the proposed provisioning technique help the cloud operators to tune the resources accordingly to match the offerings with requirements.