A Correlated Model for Evaluating Performance and Energy of Cloud System Given System Reliability

Hongli Zhang, Panpan Li and Zhigang Zhou

Discrete Dynamics in Nature and Society, 2015, vol. 2015, 1-10

Abstract:

The serious issue of energy consumption for high performance computing systems has attracted much attention. Performance and energy-saving have become important measures of a computing system. In the cloud computing environment, the systems usually allocate various resources (such as CPU, Memory, Storage, etc.) on multiple virtual machines (VMs) for executing tasks. Therefore, the problem of resource allocation for running VMs should have significant influence on both system performance and energy consumption. For different processor utilizations assigned to the VM, there exists the tradeoff between energy consumption and task completion time when a given task is executed by the VMs. Moreover, the hardware failure, software failure and restoration characteristics also have obvious influences on overall performance and energy. In this paper, a correlated model is built to analyze both performance and energy in the VM execution environment given the reliability restriction, and an optimization model is presented to derive the most effective solution of processor utilization for the VM. Then, the tradeoff between energy-saving and task completion time is studied and balanced when the VMs execute given tasks. Numerical examples are illustrated to build the performance-energy correlated model and evaluate the expected values of task completion time and consumed energy.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:497048

DOI: 10.1155/2015/497048

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