中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

30 records (took 0.018 seconds)

    Dynamic resource distribution using periodicity-aware predictive modeling
    3.
    发明授权
    Dynamic resource distribution using periodicity-aware predictive modeling 有权

    公开(公告)号：US10484301B1

    公开(公告)日：2019-11-19

    申请号：US15283004

    申请日：2016-09-30

    Applicant: Nutanix, Inc.

    Inventor： Himanshu Shukla ,  Rahul Singh ,  Abhinay Nagpal ,  Aditya Ramesh

    IPC: G06F15/173 ,  H04L12/911 ,  H04L29/08 ,  H04L12/26 ,  H04L12/24 ,  G06F9/455 ,  G06F3/06

    Abstract: Resource allocation techniques for distributed data storage. A set of distributed storage system historical resource usage measurements are collected and stored using distributed storage system measurement techniques. The resource usage metrics are associated with and/or derived from processing entities in the distributed storage computing system. An analysis module determines a training window time period corresponding to a portion of the collected distributed storage system historical resource usage measurements. The training window time period is determined so as to provide an earlier time boundary and a later time boundary that defines a periodically recurring portion of the distributed storage system historical resource usage measurements. A latest cycle of those periodically recurring measurements are then used to train a predictive model, which in turn is used to produce distributed storage system predicted resource usage characteristics. Resource allocation decisions are made based at least in part on predictions from the trained predictive model.

    SYSTEM AND METHOD FOR DYNAMIC SEARCH
    4.
    发明申请
    SYSTEM AND METHOD FOR DYNAMIC SEARCH 审中-公开

    公开(公告)号：US20190340281A1

    公开(公告)日：2019-11-07

    申请号：US15970103

    申请日：2018-05-03

    Applicant: NUTANIX, INC.

    Inventor： Atreyee Maiti ,  Bryan Crowe ,  Himanshu Shukla ,  Rahul Singh ,  Shamita Pisal ,  Shyan-Ming Perng ,  Ken Chen ,  Binny Sher Gill ,  Satish Ramachandran

    IPC: G06F17/30 ,  G06F9/455

    Abstract: A system and method include receiving, by a search system of a virtual computing system, a search query via a search console, converting the search query into a structured query, and retrieving search results based on the structured query. The system and method further include activating a subset of widgets that satisfy a condition based on the search results and determining a view for each activated widget. Each widget is configured to display a particular type of the search results and the view for each widget is based upon a number of the search results of the particular type that the widget is configured to display. The system and method additionally include displaying the activated widget on the search console according to the view of that widget.

    Storage infrastructure scenario planning
    5.
    发明授权
    Storage infrastructure scenario planning 有权

    公开(公告)号：US10361925B1

    公开(公告)日：2019-07-23

    申请号：US15191387

    申请日：2016-06-23

    Applicant: Nutanix, Inc.

    Inventor： Himanshu Shukla ,  Bharat Kumar Beedu ,  Abhinay Nagpal

    IPC: H04L12/24 ,  H04L29/08

    Abstract: Systems and methods for “what-if” scenario planning of a distributed data storage system. A scenario planning engine has a user interface to facilitate user interactions to describe “what if” scenarios. A method comprises steps to collect system performance measurements pertaining to measurable characteristics of the distributed storage system. A predictive model is generated and formatted for use as a predictor of one or more predictive model parameters that are derived from the collected system performance measurements and/or any calculated predictions and/or correlations. A user can vary a set of scenario input parameters so as to characterize one or more “what if” scenarios. The user-defined scenario input parameters are formatted and used as predictive model inputs. The predictive model is used to simulate predicted system performance parameters corresponding to respective “what-if” planning scenarios. A user interface is provided to present a graphical depiction of predicted system performance corresponding to the scenarios.

    Method for forecasting distributed resource utilization in a virtualization environment
    6.
    发明授权
    Method for forecasting distributed resource utilization in a virtualization environment 有权

    公开(公告)号：US11715025B2

    公开(公告)日：2023-08-01

    申请号：US15394654

    申请日：2016-12-29

    Applicant: Nutanix, Inc.

    Inventor： Jianjun Wen ,  Abhinay Nagpal ,  Himanshu Shukla ,  Binny Sher Gill ,  Cong Liu ,  Shuo Yang

    IPC: G06N7/01 ,  G06N5/02

    CPC classification number: G06N7/01 ,  G06N5/02

    Abstract: A method for time series analysis of time-oriented usage data pertaining to computing resources of a computing system. A method embodiment commences upon collecting time series datasets, individual ones of the time series datasets comprising time-oriented usage data of a respective individual computing resource. A plurality of prediction models are trained using portions of time-oriented data. The trained models are evaluated to determine quantitative measures pertaining to predictive accuracy. One of the trained models is selected and then applied over another time series dataset of the individual resource to generate a plurality of individual resource usage predictions. The individual resource usage predictions are used to calculate seasonally-adjusted resource usage demand amounts over a future time period. The resource usage demand amounts are compared to availability of the resource to form a runway that refers to a future time period when the resource is predicted to be demanded to its capacity.

    System and method for memory resizing in a virtual computing environment
    8.
    发明授权
    System and method for memory resizing in a virtual computing environment 有权

    公开(公告)号：US10929165B2

    公开(公告)日：2021-02-23

    申请号：US16051242

    申请日：2018-07-31

    Applicant: Nutanix, Inc.

    Inventor： Gaurav Poothia ,  Arun Navasivasakthivelsamy ,  Abhinay Nagpal ,  Miao Cui ,  Srinivas Bandi Ramesh Babu ,  Weiheng Chen ,  Himanshu Shukla

    IPC: G06F9/46 ,  G06F9/455 ,  G06F12/02 ,  G06F3/06

    Abstract: A system and method for dynamically adjusting the amount of memory allocated to a virtual machine includes generating, by a memory resizing system, a current memory usage profile for the virtual machine. The memory resizing system and the virtual machine are part of a virtual computing system and the current memory usage profile is generated by mapping, as a function of time, memory usage information from the virtual machine. The system and method also include computing an upper baseline based upon a peak memory usage in the current memory profile, updating an initial memory allocation of the virtual machine based upon the upper baseline and a predetermined threshold for obtaining an initial revised memory allocation, determining a moving average of memory usage from a historical memory usage profile, and updating the initial revised memory allocation based upon the moving average of memory usage for obtaining a final revised memory allocation.

    Adapting a pre-trained distributed resource predictive model to a target distributed computing environment
    9.
    发明授权
    Adapting a pre-trained distributed resource predictive model to a target distributed computing environment 有权

    公开(公告)号：US10691491B2

    公开(公告)日：2020-06-23

    申请号：US15298149

    申请日：2016-10-19

    Applicant: Nutanix, Inc.

    Inventor： Abhinay Nagpal ,  Aditya Ramesh ,  Himanshu Shukla ,  Rahul Singh

    IPC: G06F9/50 ,  G06N20/00

    Abstract: Systems for distributed resource system management. A first computing system operates in a first computing environment. A predictive model is trained in the first computing environment to form a trained resource performance predictive model that comprises a set of trained model parameters to capture at least computing and storage IO parameters that are responsive to execution of one or more workloads that consume computing and storage resources in the first computing environment. When the trained resource performance predictive model is deployed to a second computing environment, various computing system configuration differences, and/or workload differences and/or other differences between the first computing environment and the second computing environment are detected and measured. Responsive to the detected differences and/or measurements, some of the trained resource performance predictive model parameters are modified to adapt the trained resource performance predictive model to any of the detected and/or measured characteristics of the second computing environment.

Patent Agency Ranking