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    • 11. 发明授权
    • Performance isolation for storage clouds
    • 存储云的性能隔离
    • US08554917B2
    • 2013-10-08
    • US12859788
    • 2010-08-20
    • Sandip AgarwalaRichard J. Ayala, Jr.Sandeep GopisettySeshashayee S. Murthy
    • Sandip AgarwalaRichard J. Ayala, Jr.Sandeep GopisettySeshashayee S. Murthy
    • G06F15/173
    • G06F3/0689G06F3/0619G06F3/0665G06F9/5072
    • 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.
    • 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。
    • 12. 发明申请
    • AUTOMATED STORAGE PROVISIONING WITHIN A CLUSTERED COMPUTING ENVIRONMENT
    • 在集群计算环境中自动存储提供
    • US20120110260A1
    • 2012-05-03
    • US12915153
    • 2010-10-29
    • Kavita ChavdaDavid P. GoodmanSandeep GopisettyLarry S. McGimseyJames E. OlsonAameek Singh
    • Kavita ChavdaDavid P. GoodmanSandeep GopisettyLarry S. McGimseyJames E. OlsonAameek Singh
    • G06F12/00
    • G06F3/0689G06F3/0605G06F3/0619G06F3/0665G06F3/067
    • Embodiments of the present invention provide an approach for automatic storage planning and provisioning within a clustered computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention will receive planning input for a set of storage area network volume controllers (SVCs) within the clustered computing environment, the planning input indicating a potential load on the SVCs and its associated components. Along these lines, analytical models (e.g., from vendors) can be also used that allow for a load to be accurately estimated on the storage components. Regardless, 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. This allows for storage provisioning planning to be automated in a highly accurate fashion.
    • 本发明的实施例提供了一种用于集群计算环境(例如,云计算环境)内的自动存储规划和供应的方法。 具体地,本发明的实施例将接收针对集群计算环境内的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及其相关组件上的潜在负载。 沿着这些线路,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。 无论如何,还将收集一组存储组件(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。 这使得存储配置计划能够以高度精确的方式自动化。
    • 13. 发明申请
    • ONLINE MANAGEMENT OF HISTORICAL DATA FOR EFFICIENT REPORTING AND ANALYTICS
    • 有效报告和分析的历史数据在线管理
    • US20120054181A1
    • 2012-03-01
    • US12872964
    • 2010-08-31
    • Sandip AgarwalaSandeep GopisettyStefan Jaquel
    • Sandip AgarwalaSandeep GopisettyStefan Jaquel
    • G06F17/30
    • G06F17/30536G06F17/30516
    • 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.
    • 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。
    • 15. 发明申请
    • DATA CENTER POWER COST ACCOUNTING SYSTEM
    • 数据中心功率成本计算系统
    • US20110208622A1
    • 2011-08-25
    • US12713134
    • 2010-02-25
    • Sandeep GopisettyNagapramod MandagereSandeep Madhav Uttamchandani
    • Sandeep GopisettyNagapramod MandagereSandeep Madhav Uttamchandani
    • G06Q10/00G06Q50/00
    • G06Q50/06G06Q10/06G06Q10/067G06Q40/12
    • A data center power cost accounting system uses server and storage and cooling power consumption models and device maps, together with runtime application maps, to estimate the equipment power consumption and cooling power consumption of individual applications. An approximation of the cooling cost over a period of time, for any given application, can be pieced together by adding up the equipment utilized by the application and applying the cooling estimates obtained from computational fluid dynamics (CFD) simulations. The cooling estimates can further account for changes or variability in resource usage over time since the cooling estimates are based directly on utilization. The per application power consumption costs are obtained without having to install or depend on power measurement instruments or other hardware in the datacenters.
    • 数据中心电力成本会计系统使用服务器和存储和制冷功耗模型和设备映射以及运行时应用程序映射来估计各个应用的设备功耗和冷却功耗。 对于任何给定的应用,在一段时间内的冷却成本的近似可以通过将应用所使用的设备相加并应用从计算流体动力学(CFD)模拟获得的冷却估计来一起拼接。 冷却估计可以进一步说明随着时间的推移资源使用的变化或变化,因为冷却估计基于利用率。 无需安装或依赖于数据中心内的功率测量仪器或其他硬件即可获得每应用的功耗成本。
    • 20. 发明授权
    • Calibrating cloud computing environments
    • 校准云计算环境
    • US09323561B2
    • 2016-04-26
    • US12855780
    • 2010-08-13
    • Richard AyalaKavita ChavdaSandeep GopisettySeshashayee S. MurthyAameek Singh
    • Richard AyalaKavita ChavdaSandeep GopisettySeshashayee S. MurthyAameek Singh
    • G06F9/455G06F9/50G06F11/34H04L12/24
    • G06F9/45558G06F9/5072G06F11/3409G06F11/3433G06F11/3442G06F2009/4557G06F2209/501H04L41/14H04L41/145
    • 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.
    • 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。