Achieving efficiency both in terms of resource utilisation and energy consumption is a complex challenge, especially in large-scale wide-purpose data centers that serve cloudcomputing services. Simulation presents an appropriate solution for the development and testing of strategies that aim to improve efficiency problems before their applications in production environments. Various cloud simulators have been proposed to cover different aspects of the operation environment of cloud-computing systems. In this paper, we define the SCORE tool, which is dedicated to the simulation of energy-efficient monolithic and parallel-scheduling models and for the execution of heterogeneous, realistic and synthetic workloads. The simulator has been evaluated through empirical tests. The results of the experiments confirm that SCORE is a performant and reliable tool for testing energyefficiency, security, and scheduling strategies in cloud-computing environments.

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Carbon emissions, greenhouse gases and pollution in general are usually related to traditional factories, so the most modern computing factories have gone unnoticed for the general-public opinion. We empirically show through extensive and realistic simulation that: 1) energy consumption, and consequently CO 2 emissions, could be reduced from ∼15% to ∼60% if the correct energy-efficiency policies are applied; and 2) such energy-consumption reduction can be achieved without negatively impacting the correct operation of these infrastructures. To this end, this work is focused on the proposal and analysis of a set of energy-efficiency policies which are applied to traditional and hyper-scale data centres, as well as numerous operation environments, including: 1) the top resource managers used in industry; 2) eight energy-efficiency policies, including aggressive, fine-tuned and adaptive models; and 3) three types of workload-arrival patterns. Finally, we present a realistic analysis of the environmental impact of the application of such energy-efficiency policies on USA data centres. The presented results estimate that 11.5 million of tons of CO 2 could be saved, which is equivalent to the removal of 4.79 million of combustion cars, that is, the total car fleet of countries such as Portugal, Austria and Sweden.INDEX TERMS Energy efficiency, data centres, scheduling.

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