Conference Proceedings
Energy efficient scheduling of application components via brownout and approximate markov decision process
M Xu, R Buyya, M Maximilien (ed.), A Vallecillo (ed.), J Wang (ed.), M Oriol (ed.)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Springer | Published : 2017
Abstract
© Springer International Publishing AG 2017. Unexpected loads in Cloud data centers may trigger overloaded situation and performance degradation. To guarantee system performance, cloud computing environment is required to have the ability to handle overloads. The existing approaches, like Dynamic Voltage Frequency Scaling and VM consolidation, are effective in handling partial 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 or microservices temporarily. Moreover, brownout has been applied to reduce data center energy consump..
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Funding Acknowledgements
This work is supported by China Scholarship Council, Australia Research Council Future Fellowship and Discovery Project Grants. We thank Chenhao Qu, Adel Nadjaran Toosi and Satish Narayana Srirama for their valuable suggestions.