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公开(公告)号：US20200174904A1
公开(公告)日：2020-06-04
申请号：US16785039
申请日：2020-02-07
Applicant: VMware, Inc.
Inventor： Aalap Desai , Anant Agarwal , Alaa Shaabana , Ravi Cherukupalli , Sourav Kumar , Vikram Nair
Abstract: Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.
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Patent Agency Ranking
公开(公告)号：US10990501B2
公开(公告)日：2021-04-27
申请号：US16785039
申请日：2020-02-07
Applicant: VMware, Inc.
Inventor： Aalap Desai , Anant Agarwal , Alaa Shaabana , Ravi Cherukupalli , Sourav Kumar , Vikram Nair
Abstract: Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.
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公开(公告)号：US20210255944A1
公开(公告)日：2021-08-19
申请号：US17224201
申请日：2021-04-07
Applicant: VMware, Inc.
Inventor： Aalap Desai , Anant Agarwal , Alaa Shaabana , Ravi Cherukupalli , Sourav Kumar , Vikram Nair
Abstract: Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.
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公开(公告)号：US10585775B2
公开(公告)日：2020-03-10
申请号：US16043297
申请日：2018-07-24
Applicant: VMware, Inc.
Inventor： Aalap Desai , Anant Agarwal , Alaa Shaabana , Ravi Cherukupalli , Sourav Kumar , Vikram Nair
Abstract: Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.
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公开(公告)号：US20200034270A1
公开(公告)日：2020-01-30
申请号：US16043297
申请日：2018-07-24
Applicant: VMware, Inc.
Inventor： Aalap Desai , Anant Agarwal , Alaa Shaabana , Ravi Cherukupalli , Sourav Kumar , Vikram Nair
Abstract: Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.
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公开(公告)号：US11379341B2
公开(公告)日：2022-07-05
申请号：US17224201
申请日：2021-04-07
Applicant: VMware, Inc.
Inventor： Aalap Desai , Anant Agarwal , Alaa Shaabana , Ravi Cherukupalli , Sourav Kumar , Vikram Nair
Abstract: Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.
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