Um modelo analítico para estimar o consumo de energia de sistemas multi-camadas no nível de transação
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Universidade Federal de Goiás
In large-scale data centers, power management techniques such as Dynamic Voltage/Frequency Scaling (DVFS), virtual machine consolidation, and power-capping mechanisms promise impressive energy savings compared to traditional resource management strategies. Most of these techniques rely on coarse-grained monitoring of the workload behavior to apply their optimizations. However, coarse-grained monitoring and black box observations are not satisfactory for predicting the behavior of bursty workloads such as those observed in enterprise, Web servers. In this work, we propose an analytical model to estimate the energy consumption of multi-tier Web Systems. Differently from previous works, our model captures the consumption pattern at the level of fine-grained transactions and for each tier of the system. In addition, our model is based only on CPU utilization and server architectural parameters, which can be easily obtained in today’s production environments. We demonstrate the effectiveness of our model in a real-world experimentation environment, based on the TPC-W benchmark. Results show that our model is able to estimate the energy consumption for a Web system with an average relative error of 6.5% in the worst-case scenario, whereas more complex models of the literature present errors within the same order of magnitude.
FERREIRA, A. R. Um modelo analítico para estimar o consumo de energia de sistemas multi-camadas no nível de transação. 2017. 58 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2017.