Abstract: Virtualized application power budgeting can manage power budgeting for multiple applications in data centers. This power budgeting may be done in intelligent and/or dynamic ways and may be useful for updating power budgets, resolving conflicts in requests for power, and may improve the efficiency of the distribution of power to multiple applications. Virtualized application power budgeting can distinguish between priority applications and non-priority applications at a granular, virtual machine level and reduce the power consumption to only non-priority applications when there are power consumption conflicts. Virtualized application power budgeting may be able to determine the most efficient manner of providing power to each application in a data center. Further, virtualized application power budgeting may be able to distribute power according to application priority and other predetermined requirements and improve the efficiency of the power consumption by the devices in the data center.

Abstract: Virtualized application power budgeting can manage power budgeting for multiple applications in data centers. This power budgeting may be done in intelligent and/or dynamic ways and may be useful for updating power budgets, resolving conflicts in requests for power, and may improve the efficiency of the distribution of power to multiple applications. Virtualized application power budgeting can distinguish between priority applications and non-priority applications at a granular, virtual machine level and reduce the power consumption to only non-priority applications when there are power consumption conflicts. Virtualized application power budgeting may be able to determine the most efficient manner of providing power to each application in a data center. Further, virtualized application power budgeting may be able to distribute power according to application priority and other predetermined requirements and improve the efficiency of the power consumption by the devices in the data center.

Abstract: A final drive assembly for a machine is disclosed. The final drive assembly may comprise a motor coupled with a motor housing, a driven component rotatably mounted on the motor housing by at least one bearing, and a planetary transmission configured to transfer power from the motor to the driven component. The planetary transmission may have a stationary carrier coupled with the motor housing, and the carrier may be adapted to retain the at least one bearing.

Abstract: A final drive assembly for a machine is disclosed. The final drive assembly may comprise a motor coupled with a motor housing, a driven component rotatably mounted on the motor housing by at least one bearing, and a planetary transmission configured to transfer power from the motor to the driven component. The planetary transmission may have a stationary carrier coupled with the motor housing, and the carrier may be adapted to retain the at least one bearing.

Abstract: Virtualized application power budgeting can manage power budgeting for multiple applications in data centers. This power budgeting may be done in intelligent and/or dynamic ways and may be useful for updating power budgets, resolving conflicts in requests for power, and may improve the efficiency of the distribution of power to multiple applications. Virtualized application power budgeting can distinguish between priority applications and non-priority applications at a granular, virtual machine level and reduce the power consumption to only non-priority applications when there are power consumption conflicts. Virtualized application power budgeting may be able to determine the most efficient manner of providing power to each application in a data center. Further, virtualized application power budgeting may be able to distribute power according to application priority and other predetermined requirements and improve the efficiency of the power consumption by the devices in the data center.

Abstract: Virtualized application power budgeting can manage power budgeting for multiple applications in data centers. This power budgeting may be done in intelligent and/or dynamic ways and may be useful for updating power budgets, resolving conflicts in requests for power, and may improve the efficiency of the distribution of power to multiple applications. Virtualized application power budgeting can distinguish between priority applications and non-priority applications at a granular, virtual machine level and reduce the power consumption to only non-priority applications when there are power consumption conflicts. Virtualized application power budgeting may be able to determine the most efficient manner of providing power to each application in a data center. Further, virtualized application power budgeting may be able to distribute power according to application priority and other predetermined requirements and improve the efficiency of the power consumption by the devices in the data center.

Abstract: Provided herein is power usage estimation that may be applied to computing devices. Further, the power usage estimation may be determined per each thread, process and/or program running on the computing device, such as, for example, a virtual machine. Power meters may be associated with individual components in a computing device, the sum of the power consumption of the computing components being equal to the total power consumption of the computing device. Metrics for usage by a process may be associated with each component, from which power consumption profiles based on component usage by a process may be created. Estimations of power usage may be used in contracting, billing, ranking, system control, priority, output and the like. Estimations of power usage may also include a power consumption “learning” phase and a way of incorporating previously disregarded base power usage into the estimate of power consumption by a process.