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1.发明授权公开(公告)号：US08838779B2
公开(公告)日：2014-09-16
申请号：US12612507
申请日：2009-11-04
IPC分类号： G06F15/173 , G06F11/34
CPC分类号： G06F11/3495 , G06F11/3409 , G06F11/3447 , G06F2201/81
摘要： A method, system, and article are provided for monitoring performance of hardware devices. Each hardware device is configured with an agent, and the server is configured with a coordinator. The agent collects device data at a first modifiable frequency and communicates the collected data to the coordinator at a second dynamically modifiable frequency. The collected data is periodically monitored and the first and second frequencies are modified subject to evaluation of the collected and monitored data.
摘要翻译： 提供了一种方法，系统和文章来监视硬件设备的性能。 每个硬件设备都配置了一个代理，服务器配置了一个协调器。 代理以第一可修改频率收集设备数据，并以第二可动态修改频率将收集的数据传送给协调器。 定期监测所收集的数据，并对收集和监测的数据进行评估，对第一和第二频率进行修改。
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公开(公告)号：US20110208622A1
公开(公告)日：2011-08-25
申请号：US12713134
申请日：2010-02-25
CPC分类号： G06Q50/06 , G06Q10/06 , G06Q10/067 , G06Q40/12
摘要： 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.
摘要翻译： 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。
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公开(公告)号：US08374928B2
公开(公告)日：2013-02-12
申请号：US12713134
申请日：2010-02-25
IPC分类号： G07B17/00
CPC分类号： G06Q50/06 , G06Q10/06 , G06Q10/067 , G06Q40/12
摘要： 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.
摘要翻译： 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。
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4.发明授权公开(公告)号：US08306953B2
公开(公告)日：2012-11-06
申请号：US12872964
申请日：2010-08-31
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，用于计算历史数据的统计的方法包括访问历史数据的至少一个在线流，历史数据的在线流，包括元数据，以及从历史数据的至少一个在线流创建数据块。 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。
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5.发明申请公开(公告)号：US20110106938A1
公开(公告)日：2011-05-05
申请号：US12612507
申请日：2009-11-04
IPC分类号： G06F15/173
CPC分类号： G06F11/3495 , G06F11/3409 , G06F11/3447 , G06F2201/81
摘要： A method, system, and article are provided for monitoring performance of hardware devices. Each hardware device is configured with an agent, and the server is configured with a coordinator. The agent collects device data at a first modifiable frequency and communicates the collected data to the coordinator at a second dynamically modifiable frequency. The collected data is periodically monitored and the first and second frequencies are modified subject to evaluation of the collected and monitored data.
摘要翻译： 提供了一种方法，系统和文章来监视硬件设备的性能。 每个硬件设备都配置了一个代理，服务器配置了一个协调器。 代理以第一可修改频率收集设备数据，并以第二可动态修改频率将收集的数据传送给协调器。 定期监测所收集的数据，并对收集和监测的数据进行评估，对第一和第二频率进行修改。
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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.
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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.
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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。
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公开(公告)号：US08918439B2
公开(公告)日：2014-12-23
申请号：US12817245
申请日：2010-06-17
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。
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公开(公告)号：US08478845B2
公开(公告)日：2013-07-02
申请号：US12857005
申请日：2010-08-16
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。
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