公开(公告)号：US20120323848A1

公开(公告)日：2012-12-20

申请号：US13584509

申请日：2012-08-13

申请人： Dean Hildebrand ,  Aameek Singh ,  Renu Tewari

发明人： Dean Hildebrand ,  Aameek Singh ,  Renu Tewari

IPC分类号： G06F17/30

CPC分类号： G06F17/30578

摘要： Embodiments of the invention relate to creating and maintaining consistent data sets in a shared pool of configurable computer resources to support disaster recovery support. Data from an application is stored in local data storage and replicated to another data storage. A consistency point of the data is created in both of the data storage, with the consistency point representing an identical data set at a point-in-time. Based upon the created consistency points, a consistent set of application data may be requested to support a read operation for a migrated application.

摘要翻译： 本发明的实施例涉及在共享的可配置计算机资源池中创建和维护一致的数据集，以支持灾难恢复支持。 来自应用程序的数据存储在本地数据存储中并复制到另一个数据存储。 在两个数据存储器中创建数据的一致性点，一致点在一个时间点表示相同的数据集。 基于创建的一致性点，可以请求一致的一组应用程序数据来支持已迁移的应用程序的读取操作。

公开(公告)号：US20120278511A1

公开(公告)日：2012-11-01

申请号：US13097510

申请日：2011-04-29

申请人： Gabriel Alatorre ,  Aameek Singh

发明人： Gabriel Alatorre ,  Aameek Singh

IPC分类号： G06F13/14

CPC分类号： G06F3/0605 ,  G06F3/0646 ,  G06F3/0659 ,  G06F3/0683 ,  G06F2206/1012

摘要： Managing a data transfer from one or more source storage devices to one or more target storage devices. The data transfer comprises concurrent transfer of a multiplicity of data units pursuant to respective data transfer commands. The concurrent transfer of the multiplicity of data units is currently in-progress. A computer determines a currently-overloaded storage component involved in the data transfer. The computer determines a plurality of the data transfer commands that involve the overloaded storage component. The computer determines an approximately-minimum number of the data transfer commands to cancel to stop overload of the overloaded storage component. In response, the computer cancels the minimum number of the data transfer commands.

摘要翻译： 管理从一个或多个源存储设备到一个或多个目标存储设备的数据传输。 数据传输包括根据相应的数据传输命令并发传送多个数据单元。 目前正在进行多个数据单元的并发传输。 计算机确定数据传输中涉及的当前过载的存储组件。 计算机确定涉及过载的存储组件的多个数据传输命令。 计算机确定要取消的数据传输命令的大约最小数量，以停止过载的存储组件的过载。 作为响应，计算机取消数据传输命令的最小数量。

公开(公告)号：US20110314164A1

公开(公告)日：2011-12-22

申请号：US12817238

申请日：2010-06-17

申请人： Gabriel Alatorre ,  Eric K. Butler ,  Kavita Chavda ,  Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh

发明人： Gabriel Alatorre ,  Eric K. Butler ,  Kavita Chavda ,  Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh

IPC分类号： G06F15/16

CPC分类号： H04L67/1097 ,  H04L41/0816 ,  H04L41/145 ,  H04L43/0876

摘要： Embodiments of the present invention provide an integrated host and subsystem port selection methodology that uses performance measurements combined with information about active data paths. This technique also helps in resilient fabric planning by selecting ports from redundant fabrics. In a typical embodiment, host port to storage port pairs that create a path between a host and a storage device will be identified. From these pairs, a set of host port to storage port candidates for communicate data from the host to the storage device will be identified based on a set of resiliency constraints. Then, a specific host port to storage port pair will be selected from the set based on a lowest joint workload measurement. A path will then be created between the specific host port and storage port, and data will be communicated from the host to the storage device via the path.

摘要翻译： 本发明的实施例提供了一种集成的主机和子系统端口选择方法，其使用结合有关活动数据路径的信息的性能测量。 这种技术还通过从冗余结构中选择端口来帮助弹性布局规划。 在典型的实施例中，将识别在主机和存储设备之间创建路径的主机端口到存储端口对。 从这些对中，将基于一组弹性约束来识别从主机到存储设备的用于传送数据的存储端口候选的一组主机端口。 然后，将根据最低联合工作负载测量从集合中选择特定的主机端口到存储端口对。 然后将在特定主机端口和存储端口之间创建路径，并且数据将通过路径从主机传送到存储设备。

公开(公告)号：US08949182B2

公开(公告)日：2015-02-03

申请号：US13162615

申请日：2011-06-17

申请人： Dean Hildebrand ,  Aameek Singh ,  Renu Tewari

发明人： Dean Hildebrand ,  Aameek Singh ,  Renu Tewari

IPC分类号： G06F17/30

CPC分类号： G06F17/30578

摘要： Embodiments of the invention relate to creating and maintaining consistent data sets in a shared pool of configurable computer resources to support disaster recovery support. Data from an application is stored in local data storage and replicated to another data storage. A consistency point of the data is created in both of the data storage, with the consistency point representing an identical data set at a point-in-time. Based upon the created consistency points, a consistent set of application data may be requested to support a read operation for a migrated application.

公开(公告)号：US08495260B2

公开(公告)日：2013-07-23

申请号：US13612088

申请日：2012-09-12

申请人： Gabriel Alatorre ,  Laura Richardson ,  Aameek Singh

发明人： Gabriel Alatorre ,  Laura Richardson ,  Aameek Singh

IPC分类号： G06F17/50 ,  G06F9/45 ,  G06F3/00 ,  G06F13/28 ,  G06F13/00

CPC分类号： G06F3/0605 ,  G06F3/0646 ,  G06F3/0659 ,  G06F3/0683 ,  G06F2206/1012

摘要： Managing a data transfer from one or more source storage devices to one or more target storage devices. The data transfer comprises concurrent transfer of a multiplicity of data units pursuant to respective data transfer commands. The concurrent transfer of the multiplicity of data units is currently in-progress. A computer determines a currently-overloaded storage component involved in the data transfer. The computer determines a plurality of the data transfer commands that involve the overloaded storage component. The computer determines an approximately-minimum number of the data transfer commands to cancel to stop overload of the overloaded storage component. In response, the computer cancels the minimum number of the data transfer commands.

摘要翻译： 管理从一个或多个源存储设备到一个或多个目标存储设备的数据传输。 数据传输包括根据相应的数据传输命令并发传送多个数据单元。 目前正在进行多个数据单元的并发传输。 计算机确定数据传输中涉及的当前过载的存储组件。 计算机确定涉及过载的存储组件的多个数据传输命令。 计算机确定要取消以停止过载的存储组件的过载的数据传输命令的大致最小数量。 作为响应，计算机取消数据传输命令的最小数量。

公开(公告)号：US08489812B2

公开(公告)日：2013-07-16

申请号：US12915153

申请日：2010-10-29

申请人： Kavita Chavda ,  David P. Goodman ,  Sandeep Gopisetty ,  Larry S. McGimsey ,  James E. Olson ,  Aameek Singh

发明人： Kavita Chavda ,  David P. Goodman ,  Sandeep Gopisetty ,  Larry S. McGimsey ,  James E. Olson ,  Aameek Singh

IPC分类号： G06F12/00

CPC分类号： G06F3/0689 ,  G06F3/0605 ,  G06F3/0619 ,  G06F3/0665 ,  G06F3/067

摘要： An approach for automatic storage planning and provisioning within a clustered computing environment is provided. Planning input for a set of storage area network volume controllers (SVCs) will be received within the clustered computing environment, the planning input indicating a potential load on the SVCs and its associated components. Analytical models (e.g., from vendors) can be also used that allow for a load to be accurately estimated on the storage components. Configuration data for a set of storage components (i.e., the set of SVCs, a set of managed disk (Mdisk) groups associated with the set of SVCs, and a set of backend storage systems) will also be collected. Based on this configuration data, the set of storage components will be filtered to identify candidate storage components capable of addressing the potential load. Then, performance data for the candidate storage components will be analyzed to identify an SVC and an Mdisk group to address the potential load.

摘要翻译： 提供了一种在集群计算环境中自动存储规划和配置的方法。 将在集群计算环境内接收一组存储区域网络卷控制器（SVC）的规划输入，规划输入指示SVC及其相关组件的潜在负载。 还可以使用分析模型（例如，来自供应商），允许在存储组件上准确地估计负载。 还将收集用于一组存储组件（即，一组SVC，与该组SVC相关联的一组受管理磁盘（Mdisk）组）和一组后端存储系统的配置数据。 基于该配置数据，将对该组存储组件进行滤波以识别能够寻址潜在负载的候选存储组件。 然后，将分析候选存储组件的性能数据，以识别SVC和Mdisk组以解决潜在负载。

公开(公告)号：US20120278512A1

公开(公告)日：2012-11-01

申请号：US13097555

申请日：2011-04-29

申请人： Gabriel Alatorre ,  Laura Richardson ,  Aameek Singh

发明人： Gabriel Alatorre ,  Laura Richardson ,  Aameek Singh

IPC分类号： G06F13/14

CPC分类号： G06F3/0617 ,  G06F3/0604 ,  G06F3/0605 ,  G06F3/0647 ,  G06F3/0659 ,  G06F3/067 ,  G06F3/0685 ,  G06F9/505 ,  G06F2209/5019

摘要： Scheduling a proposed additional data transfer from one or more source storage devices to one or more target storage devices. A computer receives a request for the proposed additional data transfer, and in response, determines a measure of the proposed additional data transfer. The computer determines a measure of recent actual data transfers. The recent actual data transfers involve one or more of the source storage devices and one or more of the target storage devices. In response to the request for the proposed additional data transfer, the computer estimates performance of one or more of the source storage devices and one or more of the target storage devices that would occur during the proposed additional data transfer based on the measure of recent actual data transfers combined with the measure of the proposed additional data transfer. The computer compares the estimated performance to a corresponding performance threshold, and if less, the computer postpones execution of the proposed additional data transfer.

摘要翻译： 将建议的附加数据传输从一个或多个源存储设备调度到一个或多个目标存储设备。 计算机接收对所提出的附加数据传输的请求，作为响应，确定所提出的附加数据传输的度量。 计算机确定最近实际数据传输的度量。 最近的实际数据传输涉及一个或多个源存储设备和一个或多个目标存储设备。 响应于对所提出的附加数据传送的请求，计算机估计在所提出的附加数据传输期间将发生的一个或多个源存储设备和一个或多个目标存储设备的性能，基于最近实际的测量 数据传输与拟议的附加数据传输的量度相结合。 计算机将估计性能与相应的性能阈值进行比较，如果较少，则计算机推迟执行拟议的附加数据传输。

公开(公告)号：US20120116743A1

公开(公告)日：2012-05-10

申请号：US12942011

申请日：2010-11-08

申请人： Richard Ayala ,  Kavita Chavda ,  Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh ,  Sandeep M. Uttamchandani

发明人： Richard Ayala ,  Kavita Chavda ,  Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh ,  Sandeep M. Uttamchandani

IPC分类号： G06G7/62

CPC分类号： G06F17/30557

摘要： Embodiments of the present invention provide an approach for adapting an information extraction middleware for a clustered computing environment (e.g., a cloud environment) by creating and managing a set of statistical models generated from performance statistics of operating devices within the clustered computing environment. This approach takes into account the required accuracy in modeling, including computation cost of modeling, to pick the best modeling solution at a given point in time. When higher accuracy is desired (e.g., nearing workload saturation), the approach adapts to use an appropriate modeling algorithm. Adapting statistical models to the data characteristics ensures optimal accuracy with minimal computation time and resources for modeling. This approach provides intelligent selective refinement of models using accuracy-based and operating probability-based triggers to optimize the clustered computing environment, i.e., maximize accuracy and minimize computation time.

摘要翻译： 本发明的实施例提供了一种用于通过创建和管理从群集计算环境内的操作设备的性能统计生成的一组统计模型来适配用于群集计算环境（例如，云环境）的信息提取中间件的方法。 这种方法考虑了所需的建模精度，包括建模的计算成本，以便在给定时间点选择最佳建模解决方案。 当需要更高的精度（例如，接近工作负载饱和）时，该方法适应于使用适当的建模算法。 将统计模型适应数据特征确保最佳精度，最小的计算时间和建模资源。 该方法提供使用基于精度和基于概率的触发器来优化群集计算环境（即，最大化精度和最小化计算时间）的模型的智能选择性细化。

公开(公告)号：US20120079097A1

公开(公告)日：2012-03-29

申请号：US12893302

申请日：2010-09-29

申请人： Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh ,  Sandeep M. Uttamchandani ,  David D. Weck

发明人： Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh ,  Sandeep M. Uttamchandani ,  David D. Weck

IPC分类号： G06F15/16 ,  G06F15/173

CPC分类号： H04L43/10 ,  G06F9/5083 ,  G06F2209/508 ,  H04L67/10

摘要： The present invention proactively identifies hotspots in a cloud computing environment through cloud resource usage models that use workload parameters as inputs. In some embodiments the cloud resource usage models are based upon performance data from cloud resources and time series based workload trend models. Hotspots may occur and can be detected at any layer of the cloud computing environment, including the server, storage, and network level. In a typical embodiment, parameters for a workload are identified in the cloud computing environment and inputted into a cloud resource usage model. The model is run with the inputted workload parameters to identify potential hotspots, and resources are then provisioned for the workload so as to avoid these hotspots.

摘要翻译： 本发明通过使用工作负载参数作为输入的云资源使用模型主动地识别云计算环境中的热点。 在一些实施例中，云资源使用模型基于来自云资源和基于时间序列的工作负载趋势模型的性能数据。 热点可能会发生，并且可以在云计算环境的任何一层检测，包括服务器，存储和网络级别。 在典型的实施例中，工作负载的参数在云计算环境中被识别并被输入到云资源使用模型中。 该模型使用输入的工作负载参数运行，以识别潜在的热点，然后为工作负载提供资源，以避免这些热点。

公开(公告)号：US20120042061A1

公开(公告)日：2012-02-16

申请号：US12855780

申请日：2010-08-13

申请人： Richard Ayala ,  Kavita Chavda ,  Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh

发明人： Richard Ayala ,  Kavita Chavda ,  Sandeep Gopisetty ,  Seshashayee S. Murthy ,  Aameek Singh

IPC分类号： G06F15/173 ,  G06F9/455

CPC分类号： G06F9/45558 ,  G06F9/5072 ,  G06F11/3409 ,  G06F11/3433 ,  G06F11/3442 ,  G06F2009/4557 ,  G06F2209/501 ,  H04L41/14 ,  H04L41/145

摘要： In general, embodiments of present invention provide an approach for calibrating a cloud computing environment. Specifically, embodiments of the present invention provide an empirical approach for obtaining end-to-end performance characteristics for workloads in the cloud computing environment (hereinafter the “environment”). In a typical embodiment, different combinations of cloud server(s) and cloud storage unit(s) are determined. Then, a virtual machine is deployed to one or more of the servers within the cloud computing environment. The virtual machine is used to generate a desired workload on a set of servers within the environment. Thereafter, performance measurements for each of the different combinations under the desired workload will be taken. Among other things, the performance measurements indicate a connection quality between the set of servers and the set of storage units, and are used in calibrating the cloud computing environment to determine future workload placement. Along these lines, the performance measurements can be populated into a table or the like, and a dynamic map of a data center having the set of storage units can be generated.

摘要翻译： 通常，本发明的实施例提供了一种用于校准云计算环境的方法。 具体地，本发明的实施例提供了一种用于获得云计算环境（以下称为“环境”）中的工作负载的端到端性能特征的经验性方法。 在典型的实施例中，确定云服务器和云存储单元的不同组合。 然后，将虚拟机部署到云计算环境中的一个或多个服务器。 虚拟机用于在环境中的一组服务器上生成所需的工作负载。 此后，将采取在所需工作负荷下的每个不同组合的性能测量。 其中，性能测量表明服务器组和存储单元组之间的连接质量，并用于校准云计算环境以确定未来的工作负载布局。 沿着这些行，性能测量可以被填充到表等中，并且可以生成具有该组存储单元的数据中心的动态映射。