-
公开(公告)号：US11657256B2
公开(公告)日：2023-05-23
申请号：US17867552
申请日：2022-07-18
Applicant: Oracle International Corporation
Inventor： Pravin Shinde , Felix Schmidt , Onur Kocberber
CPC classification number: G06N3/0454 , G06F11/0709 , G06F11/0751 , G06F11/0787 , G06N3/0445 , G06N3/084 , G06N3/088 , G06F21/57 , G06F2221/034
Abstract: Embodiments use a hierarchy of machine learning models to predict datacenter behavior at multiple hardware levels of a datacenter without accessing operating system generated hardware utilization information. The accuracy of higher-level models in the hierarchy of models is increased by including, as input to the higher-level models, hardware utilization predictions from lower-level models. The hierarchy of models includes: server utilization models and workload/OS prediction models that produce predictions at a server device-level of a datacenter; and also top-of-rack switch models and backbone switch models that produce predictions at higher levels of the datacenter. These models receive, as input, hardware utilization information from non-OS sources. Based on datacenter-level network utilization predictions from the hierarchy of models, the datacenter automatically configures its hardware to avoid any predicted over-utilization of hardware in the datacenter. Also, the predictions from the hierarchy of models can be used to detect anomalies of datacenter hardware behavior.
-
公开(公告)号：US20200259722A1
公开(公告)日：2020-08-13
申请号：US16271535
申请日：2019-02-08
Applicant: Oracle International Corporation
Inventor： Onur Kocberber , Felix Schmidt , Craig Schelp , Pravin Shinde
Abstract: Herein are computerized techniques for autonomous and artificially intelligent administration of a computer cloud health monitoring system. In an embodiment, an orchestration computer automatically detects a current state of network elements of a computer network by processing: a) a network plan that defines a topology of the computer network, and b) performance statistics of the network elements. The network elements include computers that each hosts virtual execution environment(s). Each virtual execution environment hosts analysis logic that transforms raw performance data of a network element into a portion of the performance statistics. For each computer, a configuration specification for each virtual execution environment of the computer is automatically generated based on the network plan and the current state of the computer network. At least one virtual execution environment is automatically tuned and/or re-provisioned based on a generated configuration specification.
-
公开(公告)号：US10768982B2
公开(公告)日：2020-09-08
申请号：US16135802
申请日：2018-09-19
Applicant: Oracle International Corporation
Inventor： Andrew Brownsword , Tayler Hetherington , Pavan Chandrashekar , Akhilesh Singhania , Stuart Wray , Pravin Shinde , Felix Schmidt , Craig Schelp , Onur Kocberber , Juan Fernandez Peinador , Rod Reddekopp , Manel Fernandez Gomez , Nipun Agarwal
Abstract: Herein are techniques for analysis of data streams. In an embodiment, a computer associates each software actor with data streams. Each software actor has its own backlog queue of data to analyze. In response to receiving some stream content and based on the received stream content, data is distributed to some software actors. In response to determining that the data satisfies completeness criteria of a particular software actor, an indication of the data is appended onto the backlog queue of the particular software actor. The particular software actor is reset to an initial state by loading an execution snapshot of a previous initial execution of an embedded virtual machine. Based on the particular software actor, execution of the execution snapshot of the previous initial execution is resumed to dequeue and process the indication of the data from the backlog queue of the particular software actor to generate a result.
-
Patent Agency Ranking
公开(公告)号：US20220351023A1
公开(公告)日：2022-11-03
申请号：US17867552
申请日：2022-07-18
Applicant: Oracle International Corporation
Inventor： Pravin Shinde , Felix Schmidt , Onur Kocberber
Abstract: Embodiments use a hierarchy of machine learning models to predict datacenter behavior at multiple hardware levels of a datacenter without accessing operating system generated hardware utilization information. The accuracy of higher-level models in the hierarchy of models is increased by including, as input to the higher-level models, hardware utilization predictions from lower-level models. The hierarchy of models includes: server utilization models and workload/OS prediction models that produce predictions at a server device-level of a datacenter; and also top-of-rack switch models and backbone switch models that produce predictions at higher levels of the datacenter. These models receive, as input, hardware utilization information from non-OS sources. Based on datacenter-level network utilization predictions from the hierarchy of models, the datacenter automatically configures its hardware to avoid any predicted over-utilization of hardware in the datacenter. Also, the predictions from the hierarchy of models can be used to detect anomalies of datacenter hardware behavior.
-
公开(公告)号：US11443166B2
公开(公告)日：2022-09-13
申请号：US16173655
申请日：2018-10-29
Applicant: Oracle International Corporation
Inventor： Pravin Shinde , Felix Schmidt , Onur Kocberber
Abstract: Embodiments use a hierarchy of machine learning models to predict datacenter behavior at multiple hardware levels of a datacenter without accessing operating system generated hardware utilization information. The accuracy of higher-level models in the hierarchy of models is increased by including, as input to the higher-level models, hardware utilization predictions from lower-level models. The hierarchy of models includes: server utilization models and workload/OS prediction models that produce predictions at a server device-level of a datacenter; and also top-of-rack switch models and backbone switch models that produce predictions at higher levels of the datacenter. These models receive, as input, hardware utilization information from non-OS sources. Based on datacenter-level network utilization predictions from the hierarchy of models, the datacenter automatically configures its hardware to avoid any predicted over-utilization of hardware in the datacenter. Also, the predictions from the hierarchy of models can be used to detect anomalies of datacenter hardware behavior.
-
公开(公告)号：US10917203B2
公开(公告)日：2021-02-09
申请号：US16414954
申请日：2019-05-17
Applicant: Oracle International Corporation
Inventor： Stuart Wray , Felix Schmidt , Craig Schelp , Pravin Shinde , Akhilesh Singhania , Nipun Agarwal
Abstract: Embodiments use Bayesian techniques to efficiently estimate the bit error rates (BERs) of cables in a computer network at a customizable level of confidence. Specifically, a plurality of probability records are maintained for a given cable in a computer system, where each probability record is associated with a hypothetical BER for the cable, and reflects a probability that the cable has the associated hypothetical BER. At configurable time intervals, the probability records are updated using statistics gathered from a switch port connected to the cable. In order to estimate the BER of the cable at a given confidence level, embodiments determine which probability record is associated with a probability mass that indicates the confidence level. The estimate for the cable BER is the hypothetical BER that is associated with the indicated probability mass. Embodiments store the estimate in memory and utilize the estimate to aid in maintaining the computer system.
-
公开(公告)号：US10795690B2
公开(公告)日：2020-10-06
申请号：US16174582
申请日：2018-10-30
Applicant: Oracle International Corporation
Inventor： Pravin Shinde , Felix Schmidt , Craig Schelp
IPC: G06F9/44 , G06F9/445 , G06F16/901
Abstract: Herein are computerized techniques for generation, costing/scoring, optimal selection, and reporting of intermediate configurations for a datacenter change plan. In an embodiment, a computer receives a current configuration of a datacenter and a target configuration. New configurations are generated based on the current configuration. A cost function is applied to calculate a cost of each new configuration based on measuring a logical difference between the new configuration and the target configuration. A particular new configuration is selected that has a least cost. When the particular configuration satisfies the target configuration, the datacenter is reconfigured based on the particular configuration. Otherwise, this process is (e.g. iteratively) repeated with the particular configuration instead used as the current configuration. In embodiments, new configurations are randomly, greedily, and/or manually generated. In an embodiment, new configurations obey design invariants that constrain which changes and/or configurations are attainable.
-
公开(公告)号：US10892961B2
公开(公告)日：2021-01-12
申请号：US16271535
申请日：2019-02-08
Applicant: Oracle International Corporation
Inventor： Onur Kocberber , Felix Schmidt , Craig Schelp , Pravin Shinde
Abstract: Herein are computerized techniques for autonomous and artificially intelligent administration of a computer cloud health monitoring system. In an embodiment, an orchestration computer automatically detects a current state of network elements of a computer network by processing: a) a network plan that defines a topology of the computer network, and b) performance statistics of the network elements. The network elements include computers that each hosts virtual execution environment(s). Each virtual execution environment hosts analysis logic that transforms raw performance data of a network element into a portion of the performance statistics. For each computer, a configuration specification for each virtual execution environment of the computer is automatically generated based on the network plan and the current state of the computer network. At least one virtual execution environment is automatically tuned and/or re-provisioned based on a generated configuration specification.
-
-
-
-
-
-
-
Search Results
8
records
(took 0.017 seconds)
