公开(公告)号：US10203993B2

公开(公告)日：2019-02-12

申请号：US12388404

申请日：2009-02-18

申请人： Sandeep Gopisetty ,  Madhukar R. Korupolu ,  Dushmanta Mohapatra ,  Seshashayee Sankarshana Murthy ,  Aameek Singh

发明人： Sandeep Gopisetty ,  Madhukar R. Korupolu ,  Dushmanta Mohapatra ,  Seshashayee Sankarshana Murthy ,  Aameek Singh

IPC分类号： G06F9/50

摘要： The invention provides a method and system for continuous optimization of a data center. The method includes monitoring loads of storage modules, server modules and switch modules in the data center, detecting an overload condition upon a load exceeding a load threshold, combining server and storage virtualization to address storage overloads by planning allocation migration between the storage modules, to address server overloads by planning allocation migration between the server modules, to address switch overloads by planning allocation migration mix between server modules and storage modules for overload reduction, and orchestrating the planned allocation migration to reduce the overload condition in the data center.

公开(公告)号：US09679029B2

公开(公告)日：2017-06-13

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： G06F17/30

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.

公开(公告)号：US09329908B2

公开(公告)日：2016-05-03

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： G06F15/173 ,  G06F9/50

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。 热点可能发生，可以在云计算环境的任何层面检测，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：US08918439B2

公开(公告)日：2014-12-23

申请号：US12817245

申请日：2010-06-17

申请人： Gabriel Alatorre ,  Richard Ayala ,  Kavita Chavda ,  Sandeep Gopisetty ,  Aameek Singh

发明人： Gabriel Alatorre ,  Richard Ayala ,  Kavita Chavda ,  Sandeep Gopisetty ,  Aameek Singh

IPC分类号： G06F12/00 ,  G06F7/00 ,  G06F17/00 ,  G06F17/30 ,  G06F15/173 ,  G06F9/455

CPC分类号： G06F17/30082

摘要： Embodiments of the present invention provide lifecycle storage management for data within a Cloud computing environment. Specifically, a set of policies can be defined that allow for automatic valuation of the data and migration of the data between a set of storage tiers. Before a policy set is deployed, it can be assessed to determine effects it will have on cost, performance, and data location. Based on data characteristics and access patterns, a set of policy recommendations can be provided that predict the value of the data over time, and offer an improved migration strategy for moving the data between the set of storage tiers as the value of the data changes.

摘要翻译： 本发明的实施例为云计算环境中的数据提供生命周期存储管理。 具体来说，可以定义一组策略，允许数据的自动估价和一组存储层之间的数据迁移。 在部署策略集之前，可以对其进行评估，以确定其对成本，性能和数据位置的影响。 基于数据特征和访问模式，可以提供一组预测数据随时间推移的策略建议，并提供改进的迁移策略，用于随着数据值的变化在一组存储层之间移动数据。

公开(公告)号：US08478845B2

公开(公告)日：2013-07-02

申请号：US12857005

申请日：2010-08-16

申请人： Sandip Agarwala ,  Richard J. Ayala ,  Kavita Chavda ,  Sandeep Gopisetty

发明人： Sandip Agarwala ,  Richard J. Ayala ,  Kavita Chavda ,  Sandeep Gopisetty

IPC分类号： G06F15/177 ,  G06F15/167 ,  G06F15/173

CPC分类号： G06F15/177 ,  G06F3/0605 ,  G06F3/0629 ,  G06F3/067 ,  G06F9/5061 ,  H04L41/5054 ,  H04L67/1097

摘要： Embodiments discussed in this disclosure provide an integrated provisioning framework that automates the process of provisioning storage resources, end-to-end, for an enterprise storage cloud environment. Such embodiments configure and orchestrate the deployment of a user's workload and, at the same time, provide optimization across a multitude of storage cloud resources. Along these lines, input is received in the form of workload requirements and configuration information for available system resources. Based on the input, a set (at least one) of storage cloud configuration plans is developed that satisfy the workload requirements. A set of scripts is then generated that orchestrate the deployment and configuration of different software and hardware components based on the plans.

摘要翻译： 在本公开中讨论的实施例提供了一种集成供应框架，其自动化为企业存储云环境提供端到端的存储资源的过程。 这样的实施例配置和协调用户工作负载的部署，并且同时在多个存储云资源上提供优化。 沿着这些方式，以可用系统资源的工作负载需求和配置信息的形式接收输入。 基于输入，开发满足工作负载要求的一组（至少一个）存储云配置计划。 然后生成一组脚本，根据计划编排不同软件和硬件组件的部署和配置。

公开(公告)号：US20100306382A1

公开(公告)日：2010-12-02

申请号：US12476061

申请日：2009-06-01

申请人： Michael D. Cardosa ,  Sandeep Gopisetty ,  Madhukar R. Korupolu ,  Aameek Singh

发明人： Michael D. Cardosa ,  Sandeep Gopisetty ,  Madhukar R. Korupolu ,  Aameek Singh

IPC分类号： G06F15/173 ,  G06F9/455

CPC分类号： G06F9/5077 ,  G06F9/45541 ,  G06F9/45558 ,  G06F9/5038 ,  G06F9/5044 ,  G06F9/5094 ,  G06F2009/4557 ,  G06F2009/45595 ,  G06F2209/5014 ,  G06F2209/504 ,  Y02D10/22

摘要： Server consolidation using virtual machine resource tradeoffs, is provided. One implementation involves assigning a virtual machine to a target physical server based on a plurality of virtualization parameters for maximizing utility of a plurality of virtual machines and physical servers. The assigning performs resource allocation for the virtual machine based on capabilities of the target physical server and a plurality of virtual machine resource requirements. Virtualization parameters include a reservation parameter (min) representing a minimum resources required for a VM, a limit parameter (max) representing a maximum resources allowable for the VM, and a weight parameter (shares) representing a share of spare resources for the VM.

摘要翻译： 提供了使用虚拟机资源权衡的服务器整合。 一个实现包括基于用于最大化多个虚拟机和物理服务器的效用的多个虚拟化参数将虚拟机分配给目标物理服务器。 该分配基于目标物理服务器的能力和多个虚拟机资源需求来执行虚拟机的资源分配。 虚拟化参数包括表示VM所需的最小资源的预留参数（min），表示VM允许的最大资源的限制参数（max）以及表示VM的备用资源份额的权重参数（共享）。

公开(公告)号：US20100211956A1

公开(公告)日：2010-08-19

申请号：US12388404

申请日：2009-02-18

申请人： Sandeep Gopisetty ,  Madhukar R. Korupolu ,  Dushmanta Mohapatra ,  Seshashayee Sankarshana Murthy ,  Aameek Singh

发明人： Sandeep Gopisetty ,  Madhukar R. Korupolu ,  Dushmanta Mohapatra ,  Seshashayee Sankarshana Murthy ,  Aameek Singh

IPC分类号： G06F9/50

CPC分类号： G06F9/5088 ,  G06F9/505

摘要： The invention provides a method and system for continuous optimization of a data center. The method includes monitoring loads of storage modules, server modules and switch modules in the data center, detecting an overload condition upon a load exceeding a load threshold, combining server and storage virtualization to address storage overloads by planning allocation migration between the storage modules, to address server overloads by planning allocation migration between the server modules, to address switch overloads by planning allocation migration mix between server modules and storage modules for overload reduction, and orchestrating the planned allocation migration to reduce the overload condition in the data center.

摘要翻译： 本发明提供了一种数据中心连续优化的方法和系统。 该方法包括监视数据中心中的存储模块，服务器模块和交换机模块的负载，在负载超过负载阈值时检测过载状况，通过计划存储模块之间的分配迁移，结合服务器和存储虚拟化来解决存储过载问题， 地址服务器通过规划服务器模块之间的分配迁移来过载，通过规划服务器模块和存储模块之间的分配迁移组合来解决交换机过载，从而实现过载降级，并编排计划的分配迁移以减少数据中心的过载状况。

公开(公告)号：US20070185987A1

公开(公告)日：2007-08-09

申请号：US11347951

申请日：2006-02-06

申请人： Andreas Dieberger ,  Sandeep Gopisetty ,  Eser Kandogan ,  Cheryl Kieliszewski ,  Roberto Pineiro ,  Chung-hao Tan

发明人： Andreas Dieberger ,  Sandeep Gopisetty ,  Eser Kandogan ,  Cheryl Kieliszewski ,  Roberto Pineiro ,  Chung-hao Tan

IPC分类号： G06F15/173

CPC分类号： G06F11/328 ,  H04L43/045 ,  H04L67/1097

摘要： An apparatus, system, and method are disclosed for monitoring computer system components in large or complex systems. The apparatus includes an identifier module for associating at least one visual identifier with a computer system component. A function module associates one or more control functions with the visual identifier. A presentation module selectively displays the at least one identifier for the computer system component within a present view of a user interface. A monitoring module monitors the computer system component associated with the at least one identifier and modifies the identifier in response to a change in operational status for the computer system component.

摘要翻译： 公开了用于监视大型或复杂系统中的计算机系统组件的装置，系统和方法。 该装置包括用于将至少一个视觉标识符与计算机系统组件相关联的标识符模块。 功能模块将一个或多个控制功能与视觉标识符相关联。 呈现模块在用户界面的当前视图内选择性地显示计算机系统组件的至少一个标识符。 监视模块监视与所述至少一个标识符相关联的计算机系统组件，并响应于计算机系统组件的操作状态的改变来修改标识符。

公开(公告)号：US08554917B2

公开(公告)日：2013-10-08

申请号：US12859788

申请日：2010-08-20

申请人： Sandip Agarwala ,  Richard J. Ayala, Jr. ,  Sandeep Gopisetty ,  Seshashayee S. Murthy

发明人： Sandip Agarwala ,  Richard J. Ayala, Jr. ,  Sandeep Gopisetty ,  Seshashayee S. Murthy

IPC分类号： G06F15/173

CPC分类号： G06F3/0689 ,  G06F3/0619 ,  G06F3/0665 ,  G06F9/5072

摘要： Embodiments of the present invention provide performance isolation for storage clouds. Under one embodiment, workloads across a storage cloud architecture are grouped into clusters based on administrator or system input. A performance isolation domain is then created for each of the clusters, with each of the performance isolation domains comprising a set of data stores associated with a set of storage subsystems and a set of data paths that connect the set of data stores to a set of clients. Thereafter, performance isolation is provided among a set of layers of the performance isolation domains. Such performance isolation is provided by (among other things): pooling data stores from separate performance isolation domains into separate pools; assigning the pools to device adapters, RAID controller, and the set of storage subsystems; preventing workloads on the device adapters from exceeding capacities of the device adapters; mapping the set of data stores to a set of Input/Output (I/O) servers based on an I/O capacity and I/O load of the set of I/O servers; and/or pairing ports of the set of I/O servers with ports of the set of storage subsystems, the pairing being based upon availability, connectivity, I/O load, and I/O capacity.

摘要翻译： 本发明的实施例提供了用于存储云的性能隔离。 在一个实施例中，跨存储云架构的工作负载基于管理员或系统输入被分组成群集。 然后为每个集群创建性能隔离域，其中每个性能隔离域包括与一组存储子系统相关联的一组数据存储以及将该组数据存储连接到一组数据路径的一组数据路径 客户。 此后，在性能隔离域的一组层中提供性能隔离。 这种性能隔离由（除其他外）提供：将数据存储从单独的性能隔离域集中到单独的池中; 将池分配给设备适配器，RAID控制器和一组存储子系统; 防止设备适配器上的工作负载超过设备适配器的容量; 基于一组I / O服务器的I / O容量和I / O负载，将数据存储集映射到一组输入/输出（I / O）服务器; 和/或将该组I / O服务器的端口与该组存储子系统的端口配对，该配对基于可用性，连接性，I / O负载和I / O容量。

公开(公告)号：US20120054181A1

公开(公告)日：2012-03-01

申请号：US12872964

申请日：2010-08-31

申请人： Sandip Agarwala ,  Sandeep Gopisetty ,  Stefan Jaquel

发明人： Sandip Agarwala ,  Sandeep Gopisetty ,  Stefan Jaquel

IPC分类号： G06F17/30

CPC分类号： G06F17/30536 ,  G06F17/30516

摘要： Embodiments for efficiently computing complex statistics from historical time series data are provided. A hierarchical summarization method includes receiving at least one stream of data and creating data blocks from the at least one stream of data. In another embodiment, a method for computing statistics for historical data includes accessing at least one online stream of historical data, the online stream of historical data including metadata, and creating data blocks from the at least one online stream of historical data. Each data block includes a pair of timestamps indicating a sampling start time and a sampling end time, a number of data samples spanned by the data block, a SUM(X) statistic, a SUM(XX) statistic, and a SUM(XY) statistic computed for the data samples spanned by the data block. Other methods are also presented, such as methods for efficiently and accurately calculating statistical queries regarding historical data for arbitrary time ranges, among others.

摘要翻译： 提供了从历史时间序列数据有效地计算复杂统计数据的实施例。 层次聚合方法包括从所述至少一个数据流接收至少一个数据流并创建数据块。 在另一个实施例中，一种用于计算历史数据的统计量的方法包括访问历史数据的至少一个在线流，包括元数据的历史数据的在线流，以及从至少一个历史数据的在线流创建数据块。 每个数据块包括指示采样开始时间和采样结束时间的一对时间戳，由数据块跨越的数据样本的数量，SUM（X）统计量，SUM（XX）统计量和SUM（XY） 对由数据块跨越的数据样本计算的统计量。 还提出了其他方法，例如用于有效和准确地计算关于任意时间范围的历史数据的统计查询的方法等。