IDENTIFICATION OF MUTUAL INFLUENCE BETWEEN CLOUD NETWORK ENTITIES

    公开(公告)号:US20180248768A1

    公开(公告)日:2018-08-30

    申请号:US15445598

    申请日:2017-02-28

    CPC classification number: H04L41/145 H04L41/12 H04L43/08 H04L43/50

    Abstract: Disclosed is a mechanism to identify and quantify influence between data center entities across the physical, allocation, virtual, and service layers. A landscaping system builds an interaction topology. A feature selection mechanism selects metrics that correlate entities connected by the topology. The selected features are then modeled via predictive and inferential modeling techniques. The models generate interaction factors (IFs) that quantify a percentage of a metric for a cloud network entity that is caused by other cloud network entities coupled via the interaction topology. Interaction Confidence Levels (ICLs) are also calculated for the IFs to indicate a level of statistical confidence in the corresponding IF values. The IFs are then employed by a cloud infrastructure management system to optimize allocation of cloud network resources.

    Ranking system
    34.
    发明申请
    Ranking system 审中-公开

    公开(公告)号:US20170187790A1

    公开(公告)日:2017-06-29

    申请号:US14757775

    申请日:2015-12-23

    CPC classification number: H04L67/1008 H04L41/5025

    Abstract: One embodiment provides an apparatus. The apparatus includes ranker logic. The ranker logic is to rank each of a plurality of compute nodes in a data center based, at least in part, on a respective node score. Each node score is determined based, at least in part, on a utilization (U), a saturation parameter (S) and a capacity factor (Ci). The capacity factor is determined based, at least in part, on a sold capacity (Cs) related to the compute node. The ranker logic is further to select one compute node with a highest node score for placement of a received workload.

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