Reducing Energy Consumption with Dvfs for Real-Time Services in Cloud Computing

Abstract

Cloud computing has revolutionized the information technology industry by enabling elastic on demand provisioning of computing resources. The increase of Cloud computing has resulted in the organization of large-scale data centers around the world contain thousands of total nodes. This paper presents overview of cloud computing, issues in cloud computing, novel techniques, and software for distributed dynamic consolidation of Virtual Machines (VMs) in Cloud data centers. The goal is to improve the utilization of computing resources and reduce energy consumption under workload independent quality of service constraints. Dynamic VM consolidation leverages fine-grained fluctuations in the application workloads and continuously reallocates VMs using live migration to minimize the number of active physical nodes. Energy consumption is reduced by dynamically deactivating and reactivating physical nodes to meet the current resource demand. The proposed approach is distributed, scalable, and efficient in managing the energy-performance trade-off. In this paper, we introduce DVFS concept with live migration technique to improve efficiency of energy management and adaption scheme on real-time services.