公开(公告)号：US20080301333A1

公开(公告)日：2008-12-04

申请号：US11757902

申请日：2007-06-04

申请人： Eric Kevin Butler ,  Pi-Wei Chin ,  Scott J. Colbeck ,  Kaladhar Voruganti

发明人： Eric Kevin Butler ,  Pi-Wei Chin ,  Scott J. Colbeck ,  Kaladhar Voruganti

IPC分类号： G06F3/00

CPC分类号： G06F3/0635 ,  G06F3/0607 ,  G06F3/067 ,  G06F2206/1012 ,  H04L67/1002 ,  H04L67/101 ,  H04L67/1023

摘要： Provided are a system and article of manufacture for using host and storage controller port information to configure paths between a host and storage controller. Information is gathered on ports on at least one host, ports on at least one storage controller managing access to storage volumes, and at least one fabric over which the at least one host and storage controller ports connect. For at least one host port and storage controller port, information is gathered on a connection metric related to a number of paths in which the port is configured and a traffic metric indicating Input/Output (I/O) traffic at the port. A determination is made of available ports for one host and storage controller that are available to provide paths between one host and storage controller. The connection and traffic metrics for the available host ports are processed to select at least one host port. The connection and traffic metrics for the available storage controller ports are processed to select at least one storage controller port. The at least one selected host and storage controller port pair are configured to provide at least one path enabling the host to communicate with the selected storage controller port to access at least one storage volume managed by the selected storage controller.

摘要翻译： 提供了一种用于使用主机和存储控制器端口信息来配置主机和存储控制器之间的路径的系统和制品。 信息在至少一个主机上的端口上收集，至少一个存储控制器上的端口管理对存储卷的访问，以及至少一个结构，至少一个主机和存储控制器端口连接在该结构上。 对于至少一个主机端口和存储控制器端口，在与端口配置的路径数量相关的连接度量以及指示端口上的输入/输出（I / O）流量的流量度量上收集信息。 确定可用于在一个主机和存储控制器之间提供路径的一个主机和存储控制器的可用端口。 处理可用主机端口的连接和流量指标以至少选择一个主机端口。 处理可用存储控制器端口的连接和流量指标，以至少选择一个存储控制器端口。 所述至少一个选择的主机和存储控制器端口对被配置为提供至少一个路径，使得所述主机能够与所选择的存储控制器端口通信以访问由所选存储控制器管理的至少一个存储卷。

公开(公告)号：US07216207B1

公开(公告)日：2007-05-08

申请号：US10795648

申请日：2004-03-08

申请人： Nicholas Lloyd Armstrong-Crews ,  Lawrence Yiumchee Chiu ,  Patrick John Cozzi ,  Patrick Randolph Eaton ,  Prasenjit Sarkar ,  Krishnakumar Surugucchi ,  Kaladhar Voruganti

发明人： Nicholas Lloyd Armstrong-Crews ,  Lawrence Yiumchee Chiu ,  Patrick John Cozzi ,  Patrick Randolph Eaton ,  Prasenjit Sarkar ,  Krishnakumar Surugucchi ,  Kaladhar Voruganti

IPC分类号： G06F12/12 ,  G06F12/14

CPC分类号： G06F21/80 ,  G06F2221/2143 ,  G06F2221/2151

摘要： A system, program storage device, and method of optimizing data placement on a storage device, the method comprising establishing a specified time constraint for which the storage device is to delete data stored thereon; dividing a data object into a plurality of data bits; programming a block of data and the data bits with a logic operand if the storage device is incapable of deleting the data within the specified time constraint; creating an encoded block of data from the programmed block of data and the data bits; organizing the encoded block of data and the data bits in the storage device according to data deletion requirements; and removing the data bits from the storage device if the data bits are organized within a specified data deletion requirement, wherein the data bits are removed using a data shredding process, and wherein the logic operand comprises an exclusive-or (XOR) operator.

摘要翻译： 一种优化数据放置在存储设备上的系统，程序存储设备和方法，所述方法包括建立指定的时间约束，存储设备将为其删除存储在其上的数据; 将数据对象分割成多个数据位; 如果存储设备不能在指定的时间约束内删除数据，则用逻辑操作数编程数据块和数据位; 从编程的数据块和数据位创建编码的数据块; 根据数据删除要求组织存储设备中的编码数据块和数据位; 以及如果所述数据位被组织在指定的数据删除要求内，则从所述存储设备中去除所述数据位，其中使用数据切碎过程去除所述数据位，并且其中所述逻辑操作数包括异或（XOR）运算符。

公开(公告)号：US20060069863A1

公开(公告)日：2006-03-30

申请号：US10954574

申请日：2004-09-30

申请人： John Palmer ,  Sandeep Uttamchandani ,  Kaladhar Voruganti

发明人： John Palmer ,  Sandeep Uttamchandani ,  Kaladhar Voruganti

IPC分类号： G06F12/00

CPC分类号： G06F3/0653 ,  G06F3/0605 ,  G06F3/0629 ,  G06F3/0683 ,  G06F11/3457

摘要： When an alarm condition relating to a performance goal of a storage system is detected, a storage management system invokes an N-step lookahead engine for simulating operation of the storage system when there are multiple actions that could be taken by the storage system for eliminating the alarm condition. The N-step lookahead engine generates N possible system states based on a current state of the storage system. The N possible states are based on a cost model of each of the multiple actions. Each cost model is based on an action, a behavior implication of the action, a resource implication of the action and a transient cost of the action. An action is selected that generates a system state that optimizes the stability, a prerequisite and a transient cost of invoking the selected action.

公开(公告)号：US20050188074A1

公开(公告)日：2005-08-25

申请号：US10754778

申请日：2004-01-09

申请人： Kaladhar Voruganti ,  Sandeep Uttamchandani ,  Piyush Shivam

发明人： Kaladhar Voruganti ,  Sandeep Uttamchandani ,  Piyush Shivam

IPC分类号： G06F15/173 ,  H04L29/06

CPC分类号： H04L69/12

摘要： An intelligent offload engine to configure protocol processing between a host and the intelligent offload engine in order to improve optimization of protocol processing is provided. The intelligent offload engine provides for evaluating the host and the host environment to identify system parameters associated with the host and a host bus adapter card, wherein the intelligent offload engine exists at the host bus adapter card. Also, the intelligent offload engine determines the ability of the host and the intelligent offload engine to perform protocol processing according to the identified system parameters. In addition, the intelligent offload engine determines an optimal protocol processing configuration between the host and the intelligent offload engine, according to the determined ability of the host to perform protocol processing and the intelligent offload engine ability to perform protocol processing. Moreover, the intelligent offload engine implements the determined optimal protocol processing configuration.

摘要翻译： 提供了一种智能卸载引擎，用于配置主机和智能卸载引擎之间的协议处理，以提高协议处理的优化。 智能卸载引擎用于评估主机和主机环境，以识别与主机和主机总线适配卡相关的系统参数，其中智能卸载引擎存在于主机总线适配器卡上。 此外，智能卸载引擎确定主机和智能卸载引擎根据所识别的系统参数执行协议处理的能力。 另外，智能卸载引擎根据主机执行协议处理的能力和智能卸载引擎执行协议处理的能力，确定主机与智能卸载引擎之间的最优协议处理配置。 此外，智能卸载引擎执行确定的最佳协议处理配置。

公开(公告)号：US10360251B1

公开(公告)日：2019-07-23

申请号：US12613123

申请日：2009-11-05

申请人： Lakshmi Narayanan Bairavasundaram ,  Kaladhar Voruganti ,  Rukma A. Talwadker

发明人： Lakshmi Narayanan Bairavasundaram ,  Kaladhar Voruganti ,  Rukma A. Talwadker

IPC分类号： G06F16/35

摘要： A method and system for grouping and compressing system logs are described herein. A generation module residing and executing on a computer system may be configured to generate system logs containing system data important for support purposes describing the computer system, and system log metadata for describing the system logs. A grouping module residing and executing on a computer system may be configured to group system logs based on the system log metadata. Each group of system logs may comprise two or more system logs having the same or similar system log metadata. A data container is produced for each group of system logs and the data container is compressed. System logs having the same or similar system log metadata are more likely to have similar data, thus resulting in a higher degree of compression when grouped and compressed together.

公开(公告)号：US08903995B1

公开(公告)日：2014-12-02

申请号：US13553741

申请日：2012-07-19

申请人： Jayanta Basak ,  Vipul Mathur ,  Siddhartha Nandi ,  Srinivasan Narayanamurthy ,  Kaladhar Voruganti

发明人： Jayanta Basak ,  Vipul Mathur ,  Siddhartha Nandi ,  Srinivasan Narayanamurthy ,  Kaladhar Voruganti

IPC分类号： G06F15/16

CPC分类号： G06Q10/06 ,  H04L41/0636 ,  H04L43/08

摘要： A network server analyzes a change in the network, including performing a machine-learning analysis of an extrapolation space. The server accesses observed data from multiple counters that each record samples for a metric in the network. The server performs a CART (classification and regression tree) analysis of the observed data to select the counters whose metrics affect a target network performance, such as latency. The server estimates an extrapolation space based on the observed data for the selected counters. The server then performs a machine-learning analysis of the extrapolation space based on a kriging model of the selected counters.

摘要翻译： 网络服务器分析网络中的变化，包括执行外推空间的机器学习分析。 服务器访问来自多个计数器的观测数据，每个记录对网络中的度量进行记录采样。 服务器对观察到的数据执行CART（分类和回归树）分析，以选择其度量影响目标网络性能的计数器，例如延迟。 服务器根据所选计数器的观察数据估计外推空间。 然后，服务器基于所选计数器的克里金模型对外推空间进行机器学习分析。

公开(公告)号：US08868400B2

公开(公告)日：2014-10-21

申请号：US12112000

申请日：2008-04-30

申请人： Sai Rama Krishna Susarla ,  Thirumale Niranjan ,  Siddhartha Nandi ,  Craig Fulmer Everhart ,  Kaladhar Voruganti ,  Jim Voll

发明人： Sai Rama Krishna Susarla ,  Thirumale Niranjan ,  Siddhartha Nandi ,  Craig Fulmer Everhart ,  Kaladhar Voruganti ,  Jim Voll

IPC分类号： G06F9/44 ,  G06F13/10 ,  G06F13/12 ,  H04L12/24 ,  G06F11/34

CPC分类号： G06F11/3447 ,  G06F11/3414 ,  G06F11/3485 ,  G06F11/3495 ,  H04L41/145

摘要： Example embodiments provide various techniques for modeling network storage environments. To model a particular storage environment, component models that are associated with the components of the storage environment are loaded. Each component model is programmed to mathematically simulate one or more components of the storage environment. A system model is then composed from the component models and this system model is configured to simulate the storage environment.

摘要翻译： 示例性实施例提供了用于建模网络存储环境的各种技术。 要建模特定的存储环境，将加载与存储环境的组件相关联的组件模型。 每个组件模型被编程为在数学上模拟存储环境的一个或多个组件。 然后从组件模型组成系统模型，并将该系统模型配置为模拟存储环境。

公开(公告)号：US08862535B1

公开(公告)日：2014-10-14

申请号：US13272806

申请日：2011-10-13

申请人： Rukma Talwadker ,  Kaladhar Voruganti ,  David Slik

发明人： Rukma Talwadker ,  Kaladhar Voruganti ,  David Slik

IPC分类号： G05B13/04

CPC分类号： G06N5/048 ,  G05B13/04 ,  H04L67/10

摘要： In the area of storage management, service automation can be realized through the use of “MAPE” loop(s). A Planner (P) interacts with the Monitoring (M), Analysis (A) and Execution (E) components in a closed loop. For each new option or potential planning action the Planner (P) invokes the Analysis (A) component. The correctness, as well as effectiveness, of the planning decision is dependent on the Analysis (A) component. Embodiments can utilize an adaptive Analysis (A) component (i.e., an analysis component that can be retrained) that also associates a value of confidence and a corresponding error in the evaluation along with a predicted impact. The Planner (P) component uses this additional information for quoting the final impact of a particular planning action as part of an adaptive MAPE loop to provide improved resource utilization and resource management.

摘要翻译： 在存储管理方面，可以通过使用“MAPE”循环实现业务自动化。 计划员（P）在闭环中与监控（M），分析（A）和执行（E）组件进行交互。 对于每个新选项或潜在的计划操作，计划员（P）调用Analysis（A）组件。 规划决策的正确性和有效性取决于分析（A）组成部分。 实施例可以利用自适应分析（A）分量（即，可再培训的分析组件），其也将评估中的置信度和相应误差与预测的影响相关联。 计划员（P）组件使用这些附加信息来引用特定计划动作的最终影响作为自适应MAPE循环的一部分，以提供改进的资源利用和资源管理。

公开(公告)号：US08856335B1

公开(公告)日：2014-10-07

申请号：US13016898

申请日：2011-01-28

申请人： Neeraja Yadwadkar ,  Sai Rama Krishna Susarla ,  Kaladhar Voruganti ,  Rukma Ameet Talwadker ,  Vipul Mathur ,  Lakshmi Narayanan Bairavasundaram

发明人： Neeraja Yadwadkar ,  Sai Rama Krishna Susarla ,  Kaladhar Voruganti ,  Rukma Ameet Talwadker ,  Vipul Mathur ,  Lakshmi Narayanan Bairavasundaram

IPC分类号： G06F15/173 ,  H04L12/54 ,  H04L29/06 ,  G06F17/00 ,  G06F7/00

CPC分类号： 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

摘要： 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.

摘要翻译： 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。

公开(公告)号：US08661501B2

公开(公告)日：2014-02-25

申请号：US13217710

申请日：2011-08-25

申请人： Eric Kevin Butler ,  Pi-Wei Chin ,  Scott Joseph Colbeck ,  Kaladhar Voruganti

发明人： Eric Kevin Butler ,  Pi-Wei Chin ,  Scott Joseph Colbeck ,  Kaladhar Voruganti

IPC分类号： G06F17/00 ,  H04L29/06

CPC分类号： G06F11/0751 ,  G06F3/0605 ,  G06F11/0727 ,  H04L67/2852

摘要： A mechanism is provided to automatically retrieve zoning best practices from a centralized repository and to ensure that automatically generated zones do not violate these best practices. A user selects a set of hosts and storage controllers. The user also selects a guidance policy for creating the zone, and also selects a set of validation policies that must be enforced on the zone. If the user selects a guidance policy and a validation policy combination that is incompatible, the mechanism allows the user to change either the selected guidance policy or the set of validation policies. If the user has selected consistent-zoning as a guidance policy, then the mechanism automatically selects a guidance policy that does not violate the known validation policies.

摘要翻译： 提供了一种机制来自动从中央存储库中检索分区最佳做法，并确保自动生成的区域不会违反这些最佳做法。 用户选择一组主机和存储控制器。 用户还选择创建区域的指导策略，并且还选择必须在区域上强制执行的一组验证策略。 如果用户选择不兼容的指导策略和验证策略组合，则该机制允许用户更改所选择的指导策略或一组验证策略。 如果用户选择了一致的分区作为指导策略，则机制将自动选择不违反已知验证策略的指导策略。