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    SYSTEMS AND METHODS FOR TRACKING WORKING-SET ESTIMATES WITH A LIMITED RESOURCE BUDGET
    12.
    发明申请
    SYSTEMS AND METHODS FOR TRACKING WORKING-SET ESTIMATES WITH A LIMITED RESOURCE BUDGET 有权
    用有限的资源预算跟踪工作估算的系统和方法

    公开(公告)号：US20140310463A1

    公开(公告)日：2014-10-16

    申请号：US14315881

    申请日：2014-06-26

    Applicant: NetApp, Inc.

    Inventor： Gokul Soundararajan ,  Lakshmi Narayanan Bairavasundaram ,  Vipul Mathur ,  Kaladhar Voruganti

    IPC: G06F12/08

    CPC classification number: G06F12/0802 ,  G06F12/0888 ,  G06F2212/6042

    Abstract: Embodiments of the systems and techniques described here can leverage several insights into the nature of workload access patterns and the working-set behavior to reduce the memory overheads. As a result, various embodiments make it feasible to maintain running estimates of a workload's cacheability in current storage systems with limited resources. For example, some embodiments provide for a method comprising estimating cacheability of a workload based on a first working-set size estimate generated from the workload over a first monitoring interval. Then, based on the cacheability of the workload, a workload cache size can be determined. A cache then can be dynamically allocated (e.g., change, possibly frequently, the cache allocation for the workload when the current allocation and the desired workload cache size differ), within a storage system for example, in accordance with the workload cache size.

    Abstract translation: 这里描述的系统和技术的实施例可以利用对工作负载访问模式和工作集行为的性质的几个见解，以减少内存开销。 因此，各种实施例使得可以在有限的资源的当前存储系统中维持工作负载的高速缓存的运行估计。 例如，一些实施例提供了一种方法，其包括基于在第一监视间隔上从工作负载产生的第一工作集大小估计来估计工作负载的可缓存性。 然后，基于工作负载的可缓存性，可以确定工作负载高速缓存大小。 然后可以根据工作负载高速缓存大小来动态地分配高速缓存（例如，当当前分配和期望的工作负载高速缓存大小不同时，可以频繁地改变工作负载的高速缓存分配），例如在存储系统内。

    DYNAMIC CACHING TECHNIQUE FOR ADAPTIVELY CONTROLLING DATA BLOCK COPIES IN A DISTRIBUTED DATA PROCESSING SYSTEM
    13.
    发明申请
    DYNAMIC CACHING TECHNIQUE FOR ADAPTIVELY CONTROLLING DATA BLOCK COPIES IN A DISTRIBUTED DATA PROCESSING SYSTEM 有权
    用于在分布式数据处理系统中适应性地控制数据块复制的动态缓存技术

    公开(公告)号：US20140156777A1

    公开(公告)日：2014-06-05

    申请号：US13690158

    申请日：2012-11-30

    Applicant: NETAPP, INC.

    Inventor： Sethuraman Subbiah ,  Gokul Soundararajan ,  Tanya Shastri ,  Lakshmi Narayanan Bairavasundaram

    IPC: H04L29/08

    CPC classification number: H04L29/08144 ,  H04L67/1002 ,  H04L67/1097 ,  H04L67/2814 ,  H04L67/2842 ,  H04L67/2852 ,  H04L69/02

    Abstract: A dynamic caching technique adaptively controls copies of data blocks stored within caches (“cached copies”) of a caching layer distributed among servers of a distributed data processing system. A cache coordinator of the distributed system implements the dynamic caching technique to increase the cached copies of the data blocks to improve processing performance of the servers. Alternatively, the technique may decrease the cached copies to reduce storage capacity of the servers. The technique may increase the cached copies when it detects local and/or remote cache bottleneck conditions at the servers, a data popularity condition at the servers, or a shared storage bottleneck condition at the storage system. Otherwise, the technique may decrease the cached copies at the servers.

    Abstract translation: 动态缓存技术自适应地控制存储在分布式数据处理系统的服务器之间的缓存层的高速缓存（“高速缓存副本”）中的数据块的副本。 分布式系统的缓存协调器实现动态缓存技术来增加数据块的缓存副本，以提高服务器的处理性能。 或者，该技术可以减少缓存副本以减少服务器的存储容量。 当检测到服务器上的本地和/或远程高速缓存瓶颈状况，服务器上的数据流行状况或存储系统的共享存储瓶颈条件时，该技术可能会增加缓存副本。 否则，该技术可能会降低服务器上的缓存副本。

    Dynamic caching technique for adaptively controlling data block copies in a distributed data processing system
    14.
    发明授权
    Dynamic caching technique for adaptively controlling data block copies in a distributed data processing system 有权
    用于在分布式数据处理系统中自适应控制数据块副本的动态缓存技术

    公开(公告)号：US09385915B2

    公开(公告)日：2016-07-05

    申请号：US13690158

    申请日：2012-11-30

    Applicant: NetApp, Inc.

    Inventor： Sethuraman Subbiah ,  Gokul Soundararajan ,  Tanya Shastri ,  Lakshmi Narayanan Bairavasundaram

    IPC: G06F15/167 ,  H04L29/08 ,  H04L29/06

    CPC classification number: H04L29/08144 ,  H04L67/1002 ,  H04L67/1097 ,  H04L67/2814 ,  H04L67/2842 ,  H04L67/2852 ,  H04L69/02

    Abstract: A dynamic caching technique adaptively controls copies of data blocks stored within caches (“cached copies”) of a caching layer distributed among servers of a distributed data processing system. A cache coordinator of the distributed system implements the dynamic caching technique to increase the cached copies of the data blocks to improve processing performance of the servers. Alternatively, the technique may decrease the cached copies to reduce storage capacity of the servers. The technique may increase the cached copies when it detects local and/or remote cache bottleneck conditions at the servers, a data popularity condition at the servers, or a shared storage bottleneck condition at the storage system. Otherwise, the technique may decrease the cached copies at the servers.

    Abstract translation: 动态缓存技术自适应地控制存储在分布式数据处理系统的服务器之间的缓存层的高速缓存（“高速缓存副本”）中的数据块的副本。 分布式系统的缓存协调器实现动态缓存技术来增加数据块的缓存副本，以提高服务器的处理性能。 或者，该技术可以减少缓存副本以减少服务器的存储容量。 当检测到服务器上的本地和/或远程高速缓存瓶颈状况，服务器上的数据流行状况或存储系统的共享存储瓶颈条件时，该技术可能会增加缓存副本。 否则，该技术可能会降低服务器上的缓存副本。

    PROPOSED STORAGE SYSTEM SOLUTION SELECTION FOR SERVICE LEVEL OBJECTIVE MANAGEMENT
    15.
    发明申请
    PROPOSED STORAGE SYSTEM SOLUTION SELECTION FOR SERVICE LEVEL OBJECTIVE MANAGEMENT 有权
    建议存储系统解决方案选择服务水平目标管理

    公开(公告)号：US20160112504A1

    公开(公告)日：2016-04-21

    申请号：US14981730

    申请日：2015-12-28

    Applicant: NetApp, Inc.

    Inventor： Vipul Mathur ,  Neeraja Yadwadkar ,  Lakshmi Narayanan Bairavasundaram ,  Rukma Ameet Talwadker ,  Kaladhar Voruganti ,  Sai Rama Krishna Susaria

    IPC: H04L29/08 ,  H04L12/24

    CPC classification number: H04L67/1008 ,  G06F9/465 ,  G06F11/3006 ,  G06F11/3034 ,  G06F11/3409 ,  G06F11/3442 ,  G06F11/3447 ,  G06F11/3485 ,  G06F2201/81 ,  G06F2201/86 ,  H04L12/54 ,  H04L29/06 ,  H04L41/5009 ,  H04L47/70 ,  H04L67/1097 ,  Y02D10/34

    Abstract: Described herein is a system and method for dynamically managing service-level objectives (SLOs) for workloads of a cluster storage system. Proposed states/solutions of the cluster may be produced and evaluated to select one that achieves the SLOs for each workload. A planner engine may produce a state tree comprising nodes, each node representing a proposed state/solution. New nodes may be added to the state tree based on new solution types that are permitted, or nodes may be removed based on a received time constraint for executing a proposed solution or a client certification of a solution. The planner engine may call an evaluation engine to evaluate proposed states, the evaluation engine using an evaluation function that considers SLO, cost, and optimization goal characteristics to produce a single evaluation value for each proposed state. The planner engine may call a modeler engine that is trained using machine learning techniques.

    Abstract translation: 这里描述了用于动态管理用于集群存储系统的工作负载的服务级目标（SLO）的系统和方法。 可以生成和评估集群的建议状态/解决方案，以选择为每个工作负载实现SLO的状态/解决方案。 计划器引擎可以产生包括节点的状态树，每个节点表示提出的状态/解。 可以基于允许的新解决方案类型将新节点添加到状态树，或者可以基于接收到的时间约束来移除节点，以执行解决方案或解决方案的客户端认证。 计划器引擎可以调用评估引擎来评估提出的状态，评估引擎使用考虑SLO，成本和优化目标特征的评估函数，以产生每个建议状态的单个评估值。 计划器引擎可以调用使用机器学习技术训练的建模者引擎。

    Managing service level objectives for storage workloads
    16.
    发明授权
    Managing service level objectives for storage workloads 有权
    管理存储工作负载的服务级别目标

    公开(公告)号：US09223613B2

    公开(公告)日：2015-12-29

    申请号：US14484780

    申请日：2014-09-12

    Applicant: NETAPP, INC.

    Inventor： Vipul Mathur ,  Neeraja Yadwadkar ,  Lakshmi Narayanan Bairavasundaram ,  Rukma Ameet Talwadker ,  Kaladhar Voruganti ,  Sai Rama Krishna Susaria

    IPC: G06F15/173 ,  G06F9/46 ,  H04L29/06 ,  H04L12/54 ,  H04L29/08 ,  H04L12/28

    CPC classification number: H04L67/1008 ,  G06F9/465 ,  G06F11/3006 ,  G06F11/3034 ,  G06F11/3409 ,  G06F11/3442 ,  G06F11/3447 ,  G06F11/3485 ,  G06F2201/81 ,  G06F2201/86 ,  H04L12/54 ,  H04L29/06 ,  H04L41/5009 ,  H04L47/70 ,  H04L67/1097 ,  Y02D10/34

    Abstract: Described herein is a system and method for dynamically managing service-level objectives (SLOs) for workloads of a cluster storage system. Proposed states/solutions of the cluster may be produced and evaluated to select one that achieves the SLOs for each workload. A planner engine may produce a state tree comprising nodes, each node representing a proposed state/solution. New nodes may be added to the state tree based on new solution types that are permitted, or nodes may be removed based on a received time constraint for executing a proposed solution or a client certification of a solution. The planner engine may call an evaluation engine to evaluate proposed states, the evaluation engine using an evaluation function that considers SLO, cost, and optimization goal characteristics to produce a single evaluation value for each proposed state. The planner engine may call a modeler engine that is trained using machine learning techniques.

    Abstract translation: 这里描述了用于动态管理用于集群存储系统的工作负载的服务级目标（SLO）的系统和方法。 可以生成和评估集群的建议状态/解决方案，以选择为每个工作负载实现SLO的状态/解决方案。 计划器引擎可以产生包括节点的状态树，每个节点表示提出的状态/解。 可以基于允许的新解决方案类型将新节点添加到状态树，或者可以基于接收到的时间约束来移除节点，以执行解决方案或解决方案的客户端认证。 计划器引擎可以调用评估引擎来评估提出的状态，评估引擎使用考虑SLO，成本和优化目标特征的评估函数，以产生每个建议状态的单个评估值。 计划器引擎可以调用使用机器学习技术训练的建模者引擎。

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