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公开(公告)号：US11669735B2
公开(公告)日：2023-06-06
申请号：US16751127
申请日：2020-01-23
Applicant: VMware, Inc.
Inventor： Ala Shaabana , Arvind Mohan , Vikram Nair , Anant Agarwal , Aalap Desai , Ravi Kant Cherukupalli , Pawan Saxena
CPC classification number: G06N3/08 , G06F11/1476 , G06N3/006 , G06N3/044 , G06N3/045 , G06N3/088 , G06N3/082
Abstract: A system and method for automatically generating recurrent neural networks for log anomaly detection uses a controller recurrent neural network that generates an output set of hyperparameters when an input set of controller parameters is applied to the controller recurrent neural network. The output set of hyperparameters is applied to a target recurrent neural network to produce a child recurrent neural network with an architecture that is defined by the output set of hyperparameters. The child recurrent neural network is then trained, and a log classification accuracy of the child recurrent neural network is computed. Using the log classification accuracy, at least one of the controller parameters used to generate the child recurrent neural network is adjusted to produce a different input set of controller parameters to be applied to the controller recurrent neural network so that a different child recurrent neural network for log anomaly detection can 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：US11698819B2
公开(公告)日：2023-07-11
申请号：US17337524
申请日：2021-06-03
Applicant: VMWARE, INC.
Inventor： Piyush Parmar , Anant Agarwal , Vikram Nair , Aalap Desai , Rahul Chandrasekaran , Ravi kant Cherukupalli
CPC classification number: G06F9/505 , G06F9/5016 , G06F11/203 , G06F11/3414 , G06F11/3452
Abstract: A system and method for scaling resources of a secondary network for disaster recovery uses a disaster recovery notification from a primary resource manager of a primary network to a secondary resource manager of the secondary network to generate a scale-up recommendation for additional resources to the secondary network. The additional resources are based on latest resource demands of workloads on the primary network included in the disaster recovery notification. A scale-up operation for the additional resources is then executed based on the scale-up recommendation from the secondary resource manager to operate the secondary network with the additional resources to run the workloads on the secondary network.
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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：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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公开(公告)号：US11593234B2
公开(公告)日：2023-02-28
申请号：US16744876
申请日：2020-01-16
Applicant: VMware, Inc.
Inventor： Anant Agarwal , Rahul Chandrasekaran , Aalap Desai , Vikram Nair , Zhelong Pan
Abstract: A method of restarting a virtual machine (VM) running in a cluster in a first data center, in a second data center, includes: transmitting images of VMs, including a first VM, running in the cluster of hosts at a first point in time to the second data center for replication in the second data center; generating difference data representing a difference in an image of the first VM at a second point in time and the image of the first VM at the first point in time; transmitting the difference data to the second data center; setting the first VM to be inactive in the first data center; and communicating with a control plane in the second data center to set as active, and power on, a VM in the second data center using the replicated image of the first VM updated with the difference data.
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公开(公告)号：US20220318062A1
公开(公告)日：2022-10-06
申请号：US17337524
申请日：2021-06-03
Applicant: VMWARE, INC.
Inventor： PIYUSH PARMAR , Anant Agarwal , Vikram Nair , Aalap Desai , Rahul Chandrasekaran , Ravi Kant Cherukupalli
Abstract: A system and method for scaling resources of a secondary network for disaster recovery uses a disaster recovery notification from a primary resource manager of a primary network to a secondary resource manager of the secondary network to generate a scale-up recommendation for additional resources to the secondary network. The additional resources are based on latest resource demands of workloads on the primary network included in the disaster recovery notification. A scale-up operation for the additional resources is then executed based on the scale-up recommendation from the secondary resource manager to operate the secondary network with the additional resources to run the workloads on the secondary network.
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公开(公告)号：US11347521B2
公开(公告)日：2022-05-31
申请号：US16744896
申请日：2020-01-16
Applicant: VMware, Inc.
Inventor： Anant Agarwal , Rahul Chandrasekaran , Aalap Desai , Vikram Nair , Zhelong Pan
IPC: G06F9/4401 , G06F9/455 , G06F11/34
Abstract: A method of restarting a virtual machine running in a cluster of hosts in a first data center, in a second data center, wherein each virtual machine is assigned a priority level, includes: transmitting virtual machines images running in the cluster at a first time to the second data center; selecting virtual machines to be restarted in the second data center according to priority levels assigned; and for each selected virtual machine, (a) generating difference data in an image of the selected virtual machine at a second time and at the first time, (b) transmitting the difference data to the second data center, (c) setting the virtual machine inactive in the first data center, and (d) communicating with the second data center to set as active; and power on, a virtual machine in the second data center using the image of the virtual machine transmitted to the second data center.
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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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