Systems and methods for edge system resource capacity performance prediction
AssigneeDell Products L.P.
InventorsWilliam Jeffery White, Said Tabet
Life of this patent
Estimating the term…
Abstract
Managing the resource demand load for edge systems is significantly more complex than for other systems, such as cloud environments. Unlike cloud systems and other frameworks that are able to use closed-form solutions based on Poisson processes or other tractable Gaussian-based probability distributions, edge systems present complex waveforms, pareto/alpha-stable distributions, and long-range dependence. Based on elaborately designed embodiments that recognize the complexities of edge data, one can estimate scaling and multi-fractal dimensionality to determine predictive models.
Claims20
A processor-implemented method comprising:
- determining resource capacity of a resource of an edge system using a multi-fractal dimensional methodology;
- given the determined resource capacity, using a queuing-type model to determine a forecasted resource demand load that can be served by the edge system at a given blocking percentage;
- using a resource uncertainty estimation (RUE) methodology on resource-related data collected from the edge system to obtain a short-term resource demand load;
- comparing the short-term resource demand load to the forecasted resource demand load to identify a disparity between the short-term resource demand load and the forecasted resource demand load that indicates a potential issue;
- and
- responsive to detecting a disparity between the short-term resource demand load and the forecasted resource demand load, causing one or more actions to be taken to eliminate or mitigate the potential issue.
One or more information handling systems collectively comprising:
- one or more processors;
- and
- one or more non-transitory computer-readable 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:
- determining resource capacity of a resource of an edge system using a multi-fractal dimensional methodology;
- given the determined resource capacity, using a queuing-type model to determine a forecasted resource demand load that can be served by the edge system at a given blocking percentage;
- using a resource uncertainty estimation (RUE) methodology on resource-related data collected from the edge system to obtain a short-term resource demand load;
- comparing the short-term resource demand load to the forecasted resource demand load to identify a disparity between the short-term resource demand load and the forecasted resource demand load that indicates a potential issue;
- and
- responsive to detecting a disparity between the short-term resource demand load and the forecasted resource demand load, causing one or more actions to be taken to eliminate or mitigate the potential issue.
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:
- determining resource capacity of a resource of an edge system using a multi-fractal dimensional methodology;
- given the determined resource capacity, using a queuing-type model to determine a forecasted resource demand load that can be served by the edge system at a given blocking percentage;
- using a resource uncertainty estimation (RUE) methodology on resource-related data collected from the edge system to obtain a short-term resource demand load;
- comparing the short-term resource demand load to the forecasted resource demand load to identify a disparity between the short-term resource demand load and the forecasted resource demand load that indicates a potential issue;
- and
- responsive to detecting a disparity between the short-term resource demand load and the forecasted resource demand load, causing one or more actions to be taken to eliminate or mitigate the potential issue.
Dependencies are inferred from the claim text.