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Energy-aware Application Components Scheduling based on Brownout and Approximate MDP

Cloud computing environment needs to be designed to handle overloaded situation and performance degradation when unexpected loads are coming into the system. Both Dynamic Voltage Frequency Scaling and VM consolidation are effective in handling overloads, however, they cannot function when the whole data center is overloaded. Brownout has been proved to be a promising approach to relieve the overloads through deactivating application non-mandatory components temporarily. In this paper, we propose a brownout-based approximate Markov Decision Process approach to improve data center energy efficiency. The results demonstrate that our approach saves 20% energy consumption than VM consolidation approach. Compared with existing brownout approaches, our approach reduces 50% discount amount. Thus, reducing the impact on revenue of service providers.