Machine Learning
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
CoMon: a mostly-scalable monitoring system for PlanetLab
ACM SIGOPS Operating Systems Review
VirtualPower: coordinated power management in virtualized enterprise systems
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Cutting the electric bill for internet-scale systems
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Sandpiper: Black-box and gray-box resource management for virtual machines
Computer Networks: The International Journal of Computer and Telecommunications Networking
Concurrency and Computation: Practice & Experience
SEAA '13 Proceedings of the 2013 39th Euromicro Conference on Software Engineering and Advanced Applications
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In this paper, we propose a dynamic virtual machine consolidation algorithm to minimize the number of active physical servers on a data center in order to reduce energy cost. The proposed dynamic consolidation method uses the k-nearest neighbor regression algorithm to predict resource usage in each host. Based on prediction utilization, the consolidation method can determine (i) when a host becomes over-utilized (ii) when a host becomes under-utilized. Experimental results on the real workload traces from more than a thousand Planet Lab virtual machines show that the proposed technique minimizes energy consumption and maintains required performance levels.