Energy Efficient Scheduling of Cloud Application Components with Brownout
August 09, 2016 Β· Declared Dead Β· π IEEE Transactions on Sustainable Computing
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Authors
Minxian Xu, Amir Vahid Dastjerdi, Rajkumar Buyya
arXiv ID
1608.02707
Category
cs.DC: Distributed Computing
Citations
37
Venue
IEEE Transactions on Sustainable Computing
Last Checked
6 months ago
Abstract
It is common for cloud data centers meeting unexpected loads like request bursts, which may lead to overloaded situation and performance degradation. Dynamic Voltage Frequency Scaling and VM consolidation have been proved effective to manage overloads. However, they cannot function when the whole data center is overloaded. Brownout provides a promising direction to avoid overloads through configuring applications to temporarily degrade user experience. Additionally, brownout can also be applied to reduce data center energy consumption. As a complementary option for Dynamic Voltage Frequency Scaling and VM consolidation, our combined brownout approach reduces energy consumption through selectively and dynamically deactivating application optional components, which can also be applied to self-contained microservices. The results show that our approach can save more than 20% energy consumption and there are trade-offs between energy saving and discount offered to users.
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