Systems and methods for edge resource demand load estimation
Managing the resource demand load for edge systems is significantly more complex than for other systems, such as cloud environments. Embodiments herein provide edge resource demand load estimation systems and methods that inform scheduling and associated edge orchestration to ensure that edge system resource capacity is appropriately utilized. Efficient utilization allows an increased number of applications to be deployed at a reduced level of reserved resources. Also presented are embodiments of assurance mechanisms for monitoring edge resource demand load characterizations. In one or more embodiments, when an estimate or estimates are deemed to not be valid (e.g., having experienced stationary drift), updated estimates may be obtained.
1 . A processor-implemented method for estimating edge resource demand load, the method comprising:
given an application job request, in which an application job comprises a set of tasks:
determining a set of candidate edge systems for fulfilling a task from the set of tasks based upon:
(1) system resource capacity information from a set of two or more edge systems; and
(2) previously determined and deemed current resource demand values for the task, or, if no previously determined and deemed current resource demand values are available, one or more resource descriptors associated with the task;
dispatching the task to a target edge system selected from the candidate edge systems, in which the task is flagged to notify the target edge system to collect resource-related data associated with handling the task;
after receiving the resource-related data associated with handling the task that was collected by the target edge system, using a dataset comprising the resource-related data associated with handling the task to determine resource statistics for one or more edge resources for the task;
determining, for the task, one or more resource demand values for one or more edge resources using one or more of the resource statistics; and
storing the one or more resource demand values for use as previously determined and deemed current resource demand values.
2 . The processor-implemented method of claim 1 wherein the step of using the dataset comprising the resource-related data associated with handling the task to determine resource statistics for one or more edge resources for the task comprises:
using the dataset comprising the resource-related data associated with handling the task and a M-PCM-OFFD (Multivariate Probabilistic Collocation Method-Orthogonal Fractional Factorial Design) methodology to obtain the resource statistics for one or more edge resources for the task.
3 . The processor-implemented method of claim 2 wherein the dataset comprises resource-related data associated with handling the task collected from a plurality of instances of the target edge system handling the task over an evaluation time.
4 . The processor-implemented method of claim 2 wherein the dataset comprises resource-related data associated with handling the task collected from a plurality of edge systems handling the task over an evaluation time.
5 . The processor-implemented method of claim 1 wherein the one or more resource descriptors associated with the task are included in an application manifest associated with the application job request.
6 . The processor-implemented method of claim 1 wherein the one or more resource demand values for the task comprises, for each of a set of edge resources:
a lower control limit for the edge resource;
a mean for the edge resource; and
an upper control limit for the edge resource.
7 . The processor-implemented method of claim 1 wherein the resource statistics comprise, for each of a set of edge resources, a mean and a variance.
8 . The processor-implemented method of claim 1 further comprising repeating the steps of claim 1 to obtain resource demand values for each task from the set of tasks associated with the application job request.
9 . One or more information handling systems collectively comprising:
one or more processors; and
one or more non-transitory computer-readable medium or media comprising one or more sets of instructions which, when executed by at least one of the one or more processors, causes steps to be performed comprising:
given an application job request, in which an application job comprises a set of tasks:
determining a set of candidate edge systems for fulfilling a task from the set of tasks based upon:
(1) system resource capacity information from a set of two or more edge systems; and
(2) previously determined and deemed current resource demand values for the task, or, if no previously determined and deemed current resource demand values are available, one or more resource descriptors associated with the task;
dispatching the task to a target edge system selected from the candidate edge systems, in which the task is flagged to notify the target edge system to collect resource-related data associated with handling the task;
after receiving the resource-related data associated with handling the task that was collected by the target edge system, using a dataset comprising the resource-related data associated with handling the task to determine resource statistics for one or more edge resources for the task;
determining, for the task, one or more resource demand values for one or more edge resources using one or more of the resource statistics; and
storing the one or more resource demand values for use as previously determined and deemed current resource demand values.
10 . The one or more information handling systems of claim 9 wherein the step of using the dataset comprising the resource-related data associated with handling the task to determine resource statistics for one or more edge resources for the task comprises:
using the dataset comprising the resource-related data associated with handling the task and a M-PCM-OFFD (Multivariate Probabilistic Collocation Method-Orthogonal Fractional Factorial Design) methodology to obtain the resource statistics for one or more edge resources for the task.
11 . The one or more information handling systems of claim 10 wherein the dataset comprises resource-related data associated with handling the task collected from a plurality of instances of the target edge system handling the task over an evaluation time.
12 . The one or more information handling systems of claim 10 wherein the dataset comprises resource-related data associated with handling the task collected from a plurality of edge systems handling the task over an evaluation time.
13 . The one or more information handling systems of claim 9 wherein the one or more resource descriptors associated with the task are included in an application manifest associated with the application job request.
14 . The one or more information handling systems of claim 9 wherein the one or more resource demand values for the task comprises, for each of a set of edge resources:
a lower control limit for the edge resource;
a mean for the edge resource; and
an upper control limit for the edge resource.
15 . The one or more information handling systems of claim 9 wherein the one or more non-transitory computer-readable medium or media further comprise one or more sets of instructions which, when executed by at least one of the one or more processors, cause steps to be performed comprising:
repeating the steps of claim 9 to obtain resource demand values for each task from the set of tasks associated with the application job request.
16 . A non-transitory computer-readable medium or media comprising one or more sequences of instructions which, when executed by at least one processor, causes steps to be performed comprising:
given an application job request, in which an application job comprises a set of tasks:
determining a set of candidate edge systems for fulfilling a task from the set of tasks based upon:
(1) system resource capacity information from a set of two or more edge systems; and
(2) previously determined and deemed current resource demand values for the task, or, if no previously determined and deemed current resource demand values are available, one or more resource descriptors associated with the task;
dispatching the task to a target edge system selected from the candidate edge systems, in which the task is flagged to notify the target edge system to collect resource-related data associated with handling the task;
after receiving the resource-related data associated with handling the task that was collected by the target edge system, using a dataset comprising the resource-related data associated with handling the task to determine resource statistics for one or more edge resources for the task;
determining, for the task, one or more resource demand values for one or more edge resources using one or more of the resource statistics; and
storing the one or more resource demand values for use as previously determined and deemed current resource demand values.
17 . The non-transitory computer-readable medium or media of claim 16 wherein the step of using the dataset comprising the resource-related data associated with handling the task to determine resource statistics for one or more edge resources for the task comprises:
using the dataset comprising the resource-related data associated with handling the task and a M-PCM-OFFD (Multivariate Probabilistic Collocation Method-Orthogonal Fractional Factorial Design) methodology to obtain the resource statistics for one or more edge resources for the task.
18 . The non-transitory computer-readable medium or media of claim 17 wherein the dataset comprises resource-related data associated with handling the task collected from a plurality of instances of the target edge system handling the task over an evaluation time.
19 . The non-transitory computer-readable medium or media of claim 17 wherein the dataset comprises resource-related data associated with handling the task collected from a plurality of edge systems handling the task over an evaluation time.
20 . The non-transitory computer-readable medium or media of claim 16 wherein the one or more resource demand values for the task comprises, for each of a set of edge resources:
a lower control limit for the edge resource;
a mean for the edge resource; and
an upper control limit for the edge resource.