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    System and method for reducing state space in reinforced learning by using decision tree classification
    3.
    发明授权
    System and method for reducing state space in reinforced learning by using decision tree classification 有权

    公开(公告)号：US10460254B2

    公开(公告)日：2019-10-29

    申请号：US14660862

    申请日：2015-03-17

    Applicant: VMware, Inc.

    Inventor： Lei Lu ,  Pradeep Padala ,  Anne Holler ,  Xiaoyun Zhu

    IPC: G06N3/02 ,  G06N20/00 ,  G06F9/455 ,  G06N5/00

    Abstract: An automatic scaling system and method for reducing state space in reinforced learning for automatic scaling of a multi-tier application uses a state decision tree that is updated with new states of the multi-tier application. When a new state of the multi-tier application is received, the new state is placed in an existing node of the state decision tree only if a first attribute of the new state is same as a first attribute of any state contained in the existing node and a second attribute of the new state is sufficiently similar to a second attribute of each existing state contained in the existing node based on a similarity measurement of the second attribute of each state contained in the existing node with the second attribute of the new state.

    Performance-driven resource management in a distributed computer system
    4.
    发明授权
    Performance-driven resource management in a distributed computer system 有权

    公开(公告)号：US10212098B2

    公开(公告)日：2019-02-19

    申请号：US15226520

    申请日：2016-08-02

    Applicant: VMware, Inc.

    Inventor： Xiaoyun Zhu ,  Rean Griffith ,  Pradeep Padala ,  Aashish Parikh ,  Parth Shah ,  Lei Lu

    IPC: G06F9/455 ,  H04L12/911 ,  G06F9/50

    Abstract: A system and method for managing resources in a distributed computer system that includes at least one resource pool for a set of virtual machines (VMs) utilizes a set of desired individual VM-level resource settings that corresponds to target resource allocations for observed performance of an application running in the distributed computer system. The set of desired individual VM-level resource settings are determined by constructing a model for the observed application performance as a function of current VM-level resource allocations and then inverting the function to compute the target resource allocations in order to meet at least one user-defined service level objective (SLO). The set of desired individual VM-level resource settings are used to determine final RP-level resource settings for a resource pool to which the application belongs and final VM-level resource settings for the VMs running under the resource pool, which are then selectively applied.

    SYSTEM AND METHOD FOR REDUCING STATE SPACE IN REINFORCED LEARNING BY USING DECISION TREE CLASSIFICATION
    6.
    发明申请
    SYSTEM AND METHOD FOR REDUCING STATE SPACE IN REINFORCED LEARNING BY USING DECISION TREE CLASSIFICATION 审中-公开
    通过使用决策树分类来减少加强学习中的状态空间的系统和方法

    公开(公告)号：US20160275412A1

    公开(公告)日：2016-09-22

    申请号：US14660862

    申请日：2015-03-17

    Applicant: VMware, Inc.

    Inventor： Lei Lu ,  Pradeep Padala ,  Anne Holler ,  Xiaoyun Zhu

    IPC: G06N99/00 ,  G06F9/455 ,  G06N5/04

    CPC classification number: G06N20/00 ,  G06F9/45558 ,  G06F2009/4557 ,  G06N5/003

    Abstract: An automatic scaling system and method for reducing state space in reinforced learning for automatic scaling of a multi-tier application uses a state decision tree that is updated with new states of the multi-tier application. When a new state of the multi-tier application is received, the new state is placed in an existing node of the state decision tree only if a first attribute of the new state is same as a first attribute of any state contained in the existing node and a second attribute of the new state is sufficiently similar to a second attribute of each existing state contained in the existing node based on a similarity measurement of the second attribute of each state contained in the existing node with the second attribute of the new state.

    Abstract translation: 用于减少加强学习中的状态空间以自动缩放多层应用程序的自动缩放系统和方法使用用多层应用程序的新状态更新的状态决策树。 当接收到多层应用的新状态时，仅当新状态的第一属性与现有节点中包含的任何状态的第一属性相同时，才将新状态放置在状态决策树的现有节点中 并且新状态的第二属性基于包含在现有节点中的每个状态的第二属性与新状态的第二属性的相似性度量而与包含在现有节点中的每个现有状态的第二属性充分相似。

    Performance-driven resource management in a distributed computer system
    7.
    发明授权
    Performance-driven resource management in a distributed computer system 有权
    分布式计算机系统中的性能驱动型资源管理

    公开(公告)号：US09411622B2

    公开(公告)日：2016-08-09

    申请号：US13926773

    申请日：2013-06-25

    Applicant: VMware, Inc.

    Inventor： Xiaoyun Zhu ,  Rean Griffith ,  Pradeep Padala ,  Aashish Parikh ,  Parth Shah ,  Lei Lu

    IPC: G06F9/50 ,  G06F9/455

    CPC classification number: H04L47/70 ,  G06F9/45533 ,  G06F9/45558 ,  G06F9/5011 ,  G06F9/5072 ,  G06F2009/45595 ,  Y02D10/22 ,  Y02D10/36

    Abstract: A system and method for managing resources in a distributed computer system that includes at least one resource pool for a set of virtual machines (VMs) utilizes a set of desired individual VM-level resource settings that corresponds to target resource allocations for observed performance of an application running in the distributed computer system. The set of desired individual VM-level resource settings are determined by constructing a model for the observed application performance as a function of current VM-level resource allocations and then inverting the function to compute the target resource allocations in order to meet at least one user-defined service level objective (SLO). The set of desired individual VM-level resource settings are used to determine final RP-level resource settings for a resource pool to which the application belongs and final VM-level resource settings for the VMs running under the resource pool, which are then selectively applied.

    Abstract translation: 一种用于管理分布式计算机系统中的资源的系统和方法，其包括用于一组虚拟机（VM）的至少一个资源池，利用与目标资源分配相对应的一组期望的各个VM级资源设置来观察 应用程序在分布式计算机系统中运行。 通过为观察到的应用程序性能构建模型来确定所需的单个VM级资源设置的集合，作为当前VM级资源分配的函数，然后反转该功能以计算目标资源分配，以便满足至少一个用户 定义的服务级别目标（SLO）。 所需的单个VM级资源设置集用于确定应用程序所属的资源池的最终RP级资源设置，以及在资源池下运行的VM的最终VM级资源设置，然后选择性地应用 。

    PERFORMANCE-DRIVEN RESOURCE MANAGEMENT IN A DISTRIBUTED COMPUTER SYSTEM
    8.
    发明申请
    PERFORMANCE-DRIVEN RESOURCE MANAGEMENT IN A DISTRIBUTED COMPUTER SYSTEM 有权
    分布式计算机系统中的性能驱动资源管理

    公开(公告)号：US20140380307A1

    公开(公告)日：2014-12-25

    申请号：US13926773

    申请日：2013-06-25

    Applicant: VMware, Inc.

    Inventor： Xiaoyun Zhu ,  Rean Griffith ,  Pradeep Padala ,  Aashish Parikh ,  Parth Shah ,  Lei Lu

    IPC: G06F9/455

    CPC classification number: H04L47/70 ,  G06F9/45533 ,  G06F9/45558 ,  G06F9/5011 ,  G06F9/5072 ,  G06F2009/45595 ,  Y02D10/22 ,  Y02D10/36

    Abstract: A system and method for managing resources in a distributed computer system that includes at least one resource pool for a set of virtual machines (VMs) utilizes a set of desired individual VM-level resource settings that corresponds to target resource allocations for observed performance of an application running in the distributed computer system. The set of desired individual VM-level resource settings are determined by constructing a model for the observed application performance as a function of current VM-level resource allocations and then inverting the function to compute the target resource allocations in order to meet at least one user-defined service level objective (SLO). The set of desired individual VM-level resource settings are used to determine final RP-level resource settings for a resource pool to which the application belongs and final VM-level resource settings for the VMs running under the resource pool, which are then selectively applied.

    Abstract translation: 一种用于管理分布式计算机系统中的资源的系统和方法，其包括用于一组虚拟机（VM）的至少一个资源池，利用与目标资源分配相对应的一组期望的各个VM级资源设置来观察 应用程序在分布式计算机系统中运行。 通过为观察到的应用程序性能构建模型来确定所需的单个VM级资源设置的集合，作为当前VM级资源分配的函数，然后反转该功能以计算目标资源分配，以便满足至少一个用户 定义的服务级别目标（SLO）。 所需的单个VM级资源设置集用于确定应用程序所属的资源池的最终RP级资源设置，以及在资源池下运行的VM的最终VM级资源设置，然后选择性地应用 。

    PERFORMANCE-DRIVEN RESOURCE MANAGEMENT IN A DISTRIBUTED COMPUTER SYSTEM
    10.
    发明申请
    PERFORMANCE-DRIVEN RESOURCE MANAGEMENT IN A DISTRIBUTED COMPUTER SYSTEM 审中-公开
    分布式计算机系统中的性能驱动资源管理

    公开(公告)号：US20160344650A1

    公开(公告)日：2016-11-24

    申请号：US15226520

    申请日：2016-08-02

    Applicant: VMware, Inc.

    Inventor： Xiaoyun Zhu ,  Rean Griffith ,  Pradeep Padala ,  Aashish Parikh ,  Parth Shah ,  Lei Lu

    IPC: H04L12/911 ,  G06F9/455

    CPC classification number: H04L47/70 ,  G06F9/45533 ,  G06F9/45558 ,  G06F9/5011 ,  G06F9/5072 ,  G06F2009/45595 ,  Y02D10/22 ,  Y02D10/36

    Abstract: A system and method for managing resources in a distributed computer system that includes at least one resource pool for a set of virtual machines (VMs) utilizes a set of desired individual VM-level resource settings that corresponds to target resource allocations for observed performance of an application running in the distributed computer system. The set of desired individual VM-level resource settings are determined by constructing a model for the observed application performance as a function of current VM-level resource allocations and then inverting the function to compute the target resource allocations in order to meet at least one user-defined service level objective (SLO). The set of desired individual VM-level resource settings are used to determine final RP-level resource settings for a resource pool to which the application belongs and final VM-level resource settings for the VMs running under the resource pool, which are then selectively applied.

    Abstract translation: 一种用于管理分布式计算机系统中的资源的系统和方法，其包括用于一组虚拟机（VM）的至少一个资源池，利用与目标资源分配相对应的一组期望的各个VM级资源设置来观察 应用程序在分布式计算机系统中运行。 通过为观察到的应用程序性能构建模型来确定所需的单个VM级资源设置的集合，作为当前VM级资源分配的函数，然后反转该功能以计算目标资源分配，以便满足至少一个用户 定义的服务级别目标（SLO）。 所需的单个VM级资源设置集用于确定应用程序所属的资源池的最终RP级资源设置，以及在资源池下运行的VM的最终VM级资源设置，然后选择性地应用 。

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