Power and performance control of soft real-time web server clusters |
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Authors: | Luciano Bertini Daniel Mossé |
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Affiliation: | a Computing Institute, Fluminense Federal University, Niterói - RJ, Brazil b Department of Computer Science, University of Pittsburgh, Pittsburgh - PA, USA |
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Abstract: | This paper presents a novel way to control power consumption and performance in a multi-tier server cluster designed for e-commerce applications. The requests submitted to these server systems have a soft real-time constraint, given that although some can miss a pre-defined deadline, the system can still meet an agreed upon performance level. Clusters of servers are extensively used nowadays and, with the steep increase in the total power consumption in these systems, economic and environmental problems have been raised. We present ways of decreasing power expenditure, and show the implementation of a SISO (Single Input Single Output) controller that acts on the speed of all server nodes capable of dynamic voltage and frequency scaling (DVFS), with QoS (Quality of Service) being the reference setpoint. For QoS, we use the request tardiness, defined as the ratio of the end-to-end response time to the deadline, rather than the usual metric that counts missed deadlines. We adjust the servers operating frequencies to guarantee that a pre-defined p-quantile of the tardiness probability distribution of the requests meet their deadlines. Doing so we can guarantee that the QoS will be statistically p. We test this technique in a prototype multi-tier cluster, using open software, commodity hardware, and a standardized e-commerce application to generate a workload close to that of the real world. The main contribution of this paper is to empirically show the robustness of the SISO controller, presenting a sensibility analysis of its parameters. Experimental results show that our implementation outperforms other published state-of-the-art cluster implementations. |
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Keywords: | Real-time systems Server clusters Energy economy Quality of service Power-aware computing |
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