Energy-efficient Task Scheduling in Data Centers

Abstract

A data center is often also a Cloud center, which delivers its computational and storage capacity as services. To enable on-demand resource provision with elasticity and high reliability, the host machines in data centers are usually virtualized, which brings a challenging research topic, i.e., how to schedule the virtual machines (VM) on the hosts for energy efficiency. The goal of this Work is to ameliorate, through scheduling, the energy-efficiency of data center. To support this work a novel VM scheduling mechanism design and implementation will be proposed. This mechanism addresses on both load-balancing and temperature-awareness with a final goal of reducing the energy consumption of a data centre. Our scheduling scheme selects a physical machine to host a virtual machine based on the user requirements, the load on the hosts and the temperature of the hosts, while maintaining the quality of the service. The proposed scheduling mechanism on CloudSim will be finally validated, a well-known simulator that models data centers provisioning Infrastructure as a Service. For a comparative study, we also implemented other scheduling algorithms i.e., non power control, DVFS and power aware ThrMu. The experimental results show that the proposed scheduling scheme, combining the power-aware with the thermal-aware scheduling strategies, significantly reduces the energy consumption of a given Data Center because of its thermal-aware strategy and the support of VM migration mechanisms.