The present invention relates to a human workload management system and method.
We expect that this hybrid service workload broker will provide the hybrid workload management that the market will demand.
In order to assess whether it’s beneficial to move to a given workload to the cloud, workload analysis is vital.
Based on the determined allocation of workload, the workload on the information processing equipment is controlled.
The exporting places the exported disk in a workload partition space associated with the workload partition.
The policy is specified on a workload basis such that the policy is specific to the workload.
The transfer of workload and provisioning of the on-demand center may also be related to a profile of the workload or an analysis of backlog workload.
The workload is therefore very limited.
The workload distributor may increase or decrease the amount of instrumentation in relation to the workload experienced at any given time.
The present invention reduces the workload of an operator handling a load object.
reduce workload of RIS users
The brokering service system receives workload associated with the request and communicates the workload to the selected resources for processing.
The present invention makes it possible to reduce the review load of a reviewer.
The difference between the split between read and write workloads has no impact on rated workload.
The error generator receives the estimate of the workload and the measure of the actual workload on the processor core and generates an error signal.
The workload predictor generates an estimate of the workload on a processor core operative on the mobile device.
It has the advantages of providing a regular incision, causing less bleeding and pain, enabling convenient post-operative nursing while requiring no stitch or loop removal, and thus greatly reducing doctor workload.
Therefore, the processor (1) bears a reduced burden.
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