ADJUSTING CLOUD RESOURCE ALLOCATION
    85.
    发明申请

    公开(公告)号:US20180077083A1

    公开(公告)日:2018-03-15

    申请号:US15815306

    申请日:2017-11-16

    CPC classification number: H04L47/823

    Abstract: In a multi-tiered simulation configuration, a combination of predictive models is executed such that each tier in the multi-tiered simulation configuration executes at least one predictive model to produce a corresponding set of predicted events, and a predicted event from a first tier in the configuration forms an input to a next tier in the configuration. Using a subset of a selected set of predicted events outputted from a corresponding selected tier in the multi-tiered simulation configuration, a set of features is extracted, each feature in the set of features having an effect on an outcome of the simulated process. The set of features is used in a demand level prediction model to predict a threshold demand, wherein reaching the threshold demand in an actual utilization of a computing resource is indicative of a likelihood of an unforeseen rise in a demand for the computing resource after a period.

    Adjusting cloud resource allocation

    公开(公告)号:US09882836B2

    公开(公告)日:2018-01-30

    申请号:US14294663

    申请日:2014-06-03

    CPC classification number: H04L47/823

    Abstract: A method, system, and computer program product for adjusting cloud resource allocation using n-tier simulation are provided in the illustrative embodiments. In a multi-tiered simulation configuration, a combination of predictive models is executed such that each tier executes at least one predictive model to produce a corresponding set of predicted events. Each tier simulates a process that is consuming a computing resource. Using a subset of a selected set of predicted events outputted from a corresponding selected tier, a set of features is extracted. each feature in the set of features has an effect on an outcome of the simulated process. The set of features is used in a demand level prediction model to predict a threshold demand. Reaching the threshold demand in an actual utilization of the computing resource is indicative of a likelihood of an unforeseen rise in a demand for the computing resource after a period.

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