Abstract: A method, system, and device for energy efficient job scheduling in a datacenter computing environment includes a master node. The master node can periodically receive energy data from slave nodes and dynamically assign computing tasks to be executed by the slave nodes based on the energy data.

Abstract: The present disclosure describes tuning for distributed data and storage and processing systems. A device may comprise a tuner module configured to determine a distributed data and storage and processing system configuration based at least on configuration information available in the device, and to adjust the distributed data and storage and processing system configuration based on a baseline configuration. The tuner module may be further configured to then determine sample information for the distributed data and storage and processing systems derived from actual distributed data and storage and processing system operation, and to use the sample information in creating a performance model of the distributed data and storage and processing system. The tuner module may be further configured to then evaluate configuration changes to the system based on the performance model, and to determine a recommended distributed data and storage and processing system configuration based on the evaluation.

Abstract: A method, system, and device for energy efficient job scheduling in a datacenter computing environment includes a master node. The master node can periodically receive energy data from slave nodes and dynamically assign computing tasks to be executed by the slave nodes based on the energy data.