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CARPO: Correlation-aware power optimization in data center networks
Abstract Power optimization has become a key challePower optimization has become a key challenge in the design of large-scale enterprise data centers. Existing research efforts focus mainly on computer servers to lower their energy consumption, while only few studies have tried to address the energy consumption of data center networks (DCNs), which can account for 20% of the total energy consumption of a data center. In this paper, we propose CARPO, a correlation-aware power optimization algorithm that dynamically consolidates traffic flows onto a small set of links and switches in a DCN and then shuts down unused network devices for energy savings. In sharp contrast to existing work, CARPO is designed based on a key observation from the analysis of real DCN traces that the bandwidth demands of different flows do not peak at exactly the same time. As a result, if the correlations among flows are considered in consolidation, more energy savings can be achieved. In addition, CARPO integrates traffic consolidation with link rate adaptation for maximized energy savings. We implement CARPO on a hardware testbed composed of 10 virtual switches configured with a production 48-port OpenFlow switch and 8 servers. Our empirical results with Wikipedia traces demonstrate that CARPO can save up to 46% of network energy for a DCN, while having only negligible delay increases. CARPO also outperforms two state-of-the-art baselines by 19.6% and 95% on energy savings, respectively. Our simulation results with 61 flows also show the superior energy efficiency of CARPO over the baselines.gy efficiency of CARPO over the baselines.
Abstractsub Power optimization has become a key challePower optimization has become a key challenge in the design of large-scale enterprise data centers. Existing research efforts focus mainly on computer servers to lower their energy consumption, while only few studies have tried to address the energy consumption of data center networks (DCNs), which can account for 20% of the total energy consumption of a data center. In this paper, we propose CARPO, a correlation-aware power optimization algorithm that dynamically consolidates traffic flows onto a small set of links and switches in a DCN and then shuts down unused network devices for energy savings. In sharp contrast to existing work, CARPO is designed based on a key observation from the analysis of real DCN traces that the bandwidth demands of different flows do not peak at exactly the same time. As a result, if the correlations among flows are considered in consolidation, more energy savings can be achieved. In addition, CARPO integrates traffic consolidation with link rate adaptation for maximized energy savings. We implement CARPO on a hardware testbed composed of 10 virtual switches configured with a production 48-port OpenFlow switch and 8 servers. Our empirical results with Wikipedia traces demonstrate that CARPO can save up to 46% of network energy for a DCN, while having only negligible delay increases. CARPO also outperforms two state-of-the-art baselines by 19.6% and 95% on energy savings, respectively. Our simulation results with 61 flows also show the superior energy efficiency of CARPO over the baselines.gy efficiency of CARPO over the baselines.
Bibtextype inproceedings  +
Doi 10.1109/INFCOM.2012.6195471  +
Has author Xiaolong Wang + , Yao Y. + , Lu K. + , Cao Q. +
Has extra keyword Bandwidth demand + , Computer servers + , Data centers + , Enterprise data + , Hardware testbeds + , Network devices + , Power Optimization + , Rate adaptation + , Research efforts + , Sharp contrast + , Total energy consumption + , Traffic flow + , Wikipedia + , Algorithms + , Energy efficiency + , Energy utilization + , Optimization +
Isbn 9781467307758  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 1125–1133  +
Published in Proceedings - IEEE INFOCOM +
Title CARPO: Correlation-aware power optimization in data center networks +
Type conference paper  +
Year 2012 +
Creation dateThis property is a special property in this wiki. 7 November 2014 19:14:55  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 19:14:55  +
DateThis property is a special property in this wiki. 2012  +
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