US 2024/0192998 A1Published application

Smoothing termination of cloud resources

AssigneeYellowdog Ltd

InventorBenjamin Neil Deitch

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Abstract

When tasks require compute/storage resources for their execution, provide these resources in a cloud, so the tasks can be executed on cloud resources. When one or more tasks are added, additional cloud resources are required to accommodate this increased workload. Initiating new cloud resources introduces latency into the process. Exponential smoothing may slow the rate at which unused cloud resources are terminated; however, this is processor intensive. With present invention it is not necessary to track the history of multiple data points from each time interval. Rather, it is only necessary to keep record of the number of tasks that were added to the workload during the first time interval. The controller only needs to keep a record of time intervals in which new tasks are added to the workload. In the intervening intervals, in which no new tasks were added, a simplified version of exponential smoothing can be applied.

Claims8

Dependent claims

A controller configured to smooth termination of cloud resources, the controller configured to:

determine a number of tasks (At-n) that were added to a workload during a first time interval (t-n);
identify a first quantity of cloud resources unused by the end of the first time interval (t-n);
estimate a second quantity, being a subset of the first quantity, of cloud resources to be required in a second time interval (t);
and
terminate a third quantity of unused cloud resources in the second time interval (t), the third quantity of unused cloud resources equal to the first quantity of cloud resources less the second quantity of cloud resources;
wherein the second quantity of cloud resources to be required in the second time interval (t) is estimated from a number of tasks expected to be added to a workload (Ft) during the second time interval (t), the number of tasks expected to be added to the workload (Ft) during the second time interval (t) being estimated from the equation
Ft=(1−α)n-1(Ft-n+α(At-n−Ft-n))
where:
Ft-n is a number of tasks that were expected to be added to the workload during the first time interval (t-n);
n is the number of time intervals from the first time interval (t-n) to the second time interval (t);
and
α is a smoothing factor having a value between zero and one.

9 more elements

Dependencies are inferred from the claim text.