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1.发明申请公开(公告)号：US20190163720A1
公开(公告)日：2019-05-30
申请号：US15898238
申请日：2018-02-16
Applicant: VMWARE, INC.
Inventor： CHANDRASHEKHAR JHA , Jobin George , Prateek Sahu , Kumar Gaurav , Jusvinder Singh
CPC classification number: G06F17/18 , G06F16/285 , G06F17/11 , G06Q10/063
Abstract: Methods and systems predict parameters in a dataset of an identified piece of (“information technology”) IT equipment. An automated method identifies datasets IT equipment in a same category of IT equipment as a piece of IT equipment identified as having incomplete dataset information. Each dataset of IT equipment parameters are used to construct generalized linear models of different classes of IT equipment within the category of IT equipment. The class of the identified IT equipment is determined. A predicted equipment parameter of incomplete information of the identified piece of IT equipment is computed using the generalized linear model associated with the class. The predicted equipment parameter can be used to complete the dataset of the identified piece of IT equipment.
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公开(公告)号：US11113117B2
公开(公告)日：2021-09-07
申请号：US16000052
申请日：2018-06-05
Applicant: VMware, Inc.
Inventor： Chandrashekhar Jha , Kumar Gaurav , Jobin George , Jusvinder Singh , Naveen Mudnal
IPC: G06F15/173 , G06F9/50 , G06K9/62
Abstract: Various examples are disclosed for using clustering routines to extrapolate metrics to other computing resources in a cluster. One or more computing devices can classify computing resources, such as servers, based on various characteristics of the computing resources. For each class of computing resource, a clustering routine can be applied to generate clusters of the computing resources. A minimal number of metrics required to be obtained from an end user can be determined as a function of a number of the clusters. If one or more of the metrics are obtained from the end user, the metrics can be extrapolated to other computing resources in the same cluster.
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公开(公告)号：US20140282420A1
公开(公告)日：2014-09-18
申请号：US13832821
申请日：2013-03-15
Applicant: VMWARE, INC.
Inventor： Hemanth Kumar PANNEM , Amrainder Singh , Diwakar Prabhakaran , Jusvinder Singh
IPC: G06F11/36
CPC classification number: G06F11/3672 , G06F9/44589 , G06F11/3648 , G06F11/3688
Abstract: A method is provided for a proxy server to assist in the testing of a product. The method includes receiving, from the product, a first request and passing the first request to a server, receiving, from the server, a first response to the first request and passing the first response to the product, recording the first request and the first response, generating one or more second responses from one or more simulated servers based on the first request and the first response, intercepting a second request from the product, in response to the second request, matching the second request to a second response, and sending the second response to the product.
Abstract translation: 为代理服务器提供了一种帮助产品测试的方法。 该方法包括从产品接收第一请求并将第一请求传递给服务器，从服务器接收对第一请求的第一响应并将第一响应传递给产品，记录第一请求和第一请求 响应，基于所述第一请求和所述第一响应从一个或多个模拟服务器生成一个或多个第二响应，响应于所述第二请求，从所述产品截取第二请求，将所述第二请求与第二响应匹配，以及发送 对产品的第二反应。
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公开(公告)号：US20190317873A1
公开(公告)日：2019-10-17
申请号：US15952824
申请日：2018-04-13
Applicant: VMware, Inc.
Inventor： Aditya Gopisetti , Chandrashekhar Jha , Jobin Raju George , Kumar Gaurav , Jusvinder Singh
Abstract: The detection of idle virtual machines through usage pattern analysis is described. In one example, a computing device can collect utilization metrics from a virtual machine over time. The utilization metrics can be related to one or more processing usage, disk usage, network usage, and memory usage metrics, among others. The utilization metrics can be separated into a set of training metrics and a set of validation metrics, and a number of clusters can be determined based on the set of training metrics. The clusters can be used to organize the set of validation metrics into groups. Depending upon the number or overall percentage of the utilization metrics assigned to individual ones of the plurality of clusters, it is possible to determine whether or not the virtual machine is an idle virtual machine. Once identified, idle virtual machines can be shut down to conserve processing resources and costs.
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5.发明申请公开(公告)号：US20190034473A1
公开(公告)日：2019-01-31
申请号：US15811710
申请日：2017-11-14
Applicant: VMWARE, INC.
Inventor： CHANDRASHEKHAR JHA , Jobin George , Prateek Sahu , Kumar Gaurav , Jusvinder Singh
Abstract: Methods and systems are directed to detection and correction of outliers in a dataset stored in a data-storage device. The dataset comprises parameter data that may be stored and organized in the form of a data table with rows and columns of parameter values. Each column of the parameter data is searched for outlier parameter values based on the parameters values in the same column. The parameter data as a whole may be searched for outlier rows of parameter values based on first and second largest variations in the parameter data. Substitute parameter values are determined for the outlier parameter values based on non-outlier parameter values of the parameter data. The substitute parameter values and corresponding outlier parameter values may be displayed in a database management user interface that enables a user to selectively accept or reject each of the substitute parameter values for the corresponding outlier parameter values.
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Patent Agency Ranking
公开(公告)号：US11188439B2
公开(公告)日：2021-11-30
申请号：US15952824
申请日：2018-04-13
Applicant: VMware, Inc.
Inventor： Aditya Gopisetti , Chandrashekhar Jha , Jobin Raju George , Kumar Gaurav , Jusvinder Singh
Abstract: The detection of idle virtual machines through usage pattern analysis is described. In one example, a computing device can collect utilization metrics from a virtual machine over time. The utilization metrics can be related to one or more processing usage, disk usage, network usage, and memory usage metrics, among others. The utilization metrics can be separated into a set of training metrics and a set of validation metrics, and a number of clusters can be determined based on the set of training metrics. The clusters can be used to organize the set of validation metrics into groups. Depending upon the number or overall percentage of the utilization metrics assigned to individual ones of the plurality of clusters, it is possible to determine whether or not the virtual machine is an idle virtual machine. Once identified, idle virtual machines can be shut down to conserve processing resources and costs.
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7.发明授权公开(公告)号：US10474667B2
公开(公告)日：2019-11-12
申请号：US15811710
申请日：2017-11-14
Applicant: VMWARE, INC.
Inventor： Chandrashekhar Jha , Jobin George , Prateek Sahu , Kumar Gaurav , Jusvinder Singh
IPC: G06F16/23 , G06F3/06 , G06F16/25 , G06F16/22 , G06F16/951
Abstract: Methods and systems are directed to detection and correction of outliers in a dataset stored in a data-storage device. The dataset comprises parameter data that may be stored and organized in the form of a data table with rows and columns of parameter values. Each column of the parameter data is searched for outlier parameter values based on the parameters values in the same column. The parameter data as a whole may be searched for outlier rows of parameter values based on first and second largest variations in the parameter data. Substitute parameter values are determined for the outlier parameter values based on non-outlier parameter values of the parameter data. The substitute parameter values and corresponding outlier parameter values may be displayed in a database management user interface that enables a user to selectively accept or reject each of the substitute parameter values for the corresponding outlier parameter values.
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8.发明授权公开(公告)号：US11651050B2
公开(公告)日：2023-05-16
申请号：US16866664
申请日：2020-05-05
Applicant: VMware, Inc.
Inventor： Chandrashekhar Jha , Jobin George , Prateek Sahu , Kumar Gaurav , Jusvinder Singh
IPC: G06F17/18 , G06Q10/063 , G06F17/11 , G06F16/28
CPC classification number: G06F17/18 , G06F16/285 , G06F17/11 , G06Q10/063
Abstract: Methods and systems predict parameters in a dataset of an identified piece of (“information technology”) IT equipment. An automated method identifies datasets IT equipment in a same category of IT equipment as a piece of IT equipment identified as having incomplete dataset information. Each dataset of IT equipment parameters is used to construct generalized linear models of different classes of IT equipment within the category of IT equipment. The class of the identified IT equipment is determined. A predicted equipment parameter of incomplete information of the identified piece of IT equipment is computed using the generalized linear model associated with the class. The predicted equipment parameter can be used to complete the dataset of the identified piece of IT equipment.
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9.发明申请公开(公告)号：US20200265111A1
公开(公告)日：2020-08-20
申请号：US16866664
申请日：2020-05-05
Applicant: VMware, Inc.
Inventor： Chandrashekhar Jha , Jobin George , Prateek Sahu , Kumar Gaurav , Jusvinder Singh
Abstract: Methods and systems predict parameters in a dataset of an identified piece of (“information technology”) IT equipment. An automated method identifies datasets IT equipment in a same category of IT equipment as a piece of IT equipment identified as having incomplete dataset information. Each dataset of IT equipment parameters is used to construct generalized linear models of different classes of IT equipment within the category of IT equipment. The class of the identified IT equipment is determined. A predicted equipment parameter of incomplete information of the identified piece of IT equipment is computed using the generalized linear model associated with the class. The predicted equipment parameter can be used to complete the dataset of the identified piece of IT equipment.
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10.发明授权公开(公告)号：US10678888B2
公开(公告)日：2020-06-09
申请号：US15898238
申请日：2018-02-16
Applicant: VMWARE, INC.
Inventor： Chandrashekhar Jha , Jobin George , Prateek Sahu , Kumar Gaurav , Jusvinder Singh
Abstract: Methods and systems predict parameters in a dataset of an identified piece of (“information technology”) IT equipment. An automated method identifies datasets IT equipment in a same category of IT equipment as a piece of IT equipment identified as having incomplete dataset information. Each dataset of IT equipment parameters are used to construct generalized linear models of different classes of IT equipment within the category of IT equipment. The class of the identified IT equipment is determined. A predicted equipment parameter of incomplete information of the identified piece of IT equipment is computed using the generalized linear model associated with the class. The predicted equipment parameter can be used to complete the dataset of the identified piece of IT equipment.
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