Abstract: To improve resource utilization and reduce the virtual machine sprawl in a data center, resource utilization is predicted based on previously measured utilizations, and then, using the predicted utilizations, optimizing the allocation of the computing resources among the virtual machines in the data center. In operation, measurements related to resource utilization by different virtual machines executing in a data center are collected at regular intervals. At each interval, an optimization system predicts virtual machine resource utilizations based on previously collected measurements and previously-generated virtual machine modelers. Based on the utilization predictions as well as the physical topology of the data center, the optimization system identifies different optimizations to the virtual machine topology for the next interval.

Abstract: To improve resource utilization and reduce the virtual machine sprawl in a data center, resource utilization is predicted based on previously measured utilizations, and then, using the predicted utilizations, optimizing the allocation of the computing resources among the virtual machines in the data center. In operation, measurements related to resource utilization by different virtual machines executing in a data center are collected at regular intervals. At each interval, an optimization system predicts virtual machine resource utilizations based on previously collected measurements and previously-generated virtual machine modelers. Based on the utilization predictions as well as the physical topology of the data center, the optimization system identifies different optimizations to the virtual machine topology for the next interval.

Abstract: To improve resource utilization and reduce the virtual machine sprawl in a data center, resource utilization is predicted based on previously measured utilizations, and then, using the predicted utilizations, optimizing the allocation of the computing resources among the virtual machines in the data center. In operation, measurements related to resource utilization by different virtual machines executing in a data center are collected at regular intervals. At each interval, an optimization system predicts virtual machine resource utilizations based on previously collected measurements and previously-generated virtual machine modelers. Based on the utilization predictions as well as the physical topology of the data center, the optimization system identifies different optimizations to the virtual machine topology for the next interval.

Abstract: To improve resource utilization and reduce the virtual machine sprawl in a data center, resource utilization is predicted based on previously measured utilizations, and then, using the predicted utilizations, optimizing the allocation of the computing resources among the virtual machines in the data center. In operation, measurements related to resource utilization by different virtual machines executing in a data center are collected at regular intervals. At each interval, an optimization system predicts virtual machine resource utilizations based on previously collected measurements and previously-generated virtual machine modelers. Based on the utilization predictions as well as the physical topology of the data center, the optimization system identifies different optimizations to the virtual machine topology for the next interval.