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1. 发明授权

US08386410B2 System and method for semantic information extraction framework for integrated systems management 失效
标题翻译：综合系统管理语义信息提取框架的系统与方法
公开(公告)号：US08386410B2
公开(公告)日：2013-02-26
申请号：US12507630
申请日：2009-07-22
申请人： Sandeep Gopisetty , Ramani R. Routray , Aameek Singh , Sandeep M. Uttamchandani
发明人： Sandeep Gopisetty , Ramani R. Routray , Aameek Singh , Sandeep M. Uttamchandani
IPC分类号： G06F17/00 , G06N5/02
CPC分类号： G06Q10/10 , H04L41/0213 , H04L41/142
摘要： The invention provides an enterprise administration system and method. The system includes a user interface module configured to enter administration terms or select a predetermined script of administration terms, a knowledge base configured to store system information, a meta information module configured to use the system information to store entity-objective indexes, and a workflow mapping module configured to map the administration terms to system information extraction tasks to extract relevant entities and objectives and apply a rule to the extracted entities and objectives for presenting the extracted entities and objectives in a ranked order.
摘要翻译：本发明提供了一种企业管理系统和方法。该系统包括被配置为输入管理术语或选择管理术语的预定脚本的用户界面模块，被配置为存储系统信息的知识库，被配置为使用系统信息来存储实体目标索引的元信息模块和工作流映射模块被配置为将管理术语映射到系统信息提取任务以提取相关实体和目标，并将规则应用于提取的实体和目标，以排列顺序呈现提取的实体和目标。

2. 发明申请

US20110022562A1 SYSTEM AND METHOD FOR SEMANTIC INFORMATION EXTRACTION FRAMEWORK FOR INTEGRATED SYSTEMS MANAGEMENT 失效
标题翻译：用于集成系统管理的语义信息提取框架的系统和方法
公开(公告)号：US20110022562A1
公开(公告)日：2011-01-27
申请号：US12507630
申请日：2009-07-22
申请人： Sandeep Gopisetty , Ramani R. Routray , Aameek Singh , Sandeep M. Uttamchandani
发明人： Sandeep Gopisetty , Ramani R. Routray , Aameek Singh , Sandeep M. Uttamchandani
IPC分类号： G06N5/02 , G06F17/30
CPC分类号： G06Q10/10 , H04L41/0213 , H04L41/142
摘要： The invention provides an enterprise administration system and method. The system includes a user interface module configured to enter administration terms or select a predetermined script of administration terms, a knowledge base configured to store system information, a meta information module configured to use the system information to store entity-objective indexes, and a workflow mapping module configured to map the administration terms to system information extraction tasks to extract relevant entities and objectives and apply a rule to the extracted entities and objectives for presenting the extracted entities and objectives in a ranked order.
摘要翻译：本发明提供了一种企业管理系统和方法。该系统包括被配置为输入管理术语或选择管理术语的预定脚本的用户界面模块，被配置为存储系统信息的知识库，被配置为使用系统信息来存储实体目标索引的元信息模块和工作流映射模块被配置为将管理术语映射到系统信息提取任务以提取相关实体和目标，并将规则应用于提取的实体和目标，以排列顺序呈现提取的实体和目标。

3. 发明申请

US20100106538A1 DETERMINING DISASTER RECOVERY SERVICE LEVEL AGREEMENTS FOR DATA COMPONENTS OF AN APPLICATION 审中-公开
标题翻译：确定应用程序数据组件的灾难恢复服务级别协议
公开(公告)号：US20100106538A1
公开(公告)日：2010-04-29
申请号：US12256799
申请日：2008-10-23
申请人： Ramani R. Routray , Upendra Sharma , Aameek Singh , Sandeep M. Uttamchandani , Akshat Verma
发明人： Ramani R. Routray , Upendra Sharma , Aameek Singh , Sandeep M. Uttamchandani , Akshat Verma
IPC分类号： G06Q10/00 , G06Q50/00
CPC分类号： G06Q10/06 , G06Q10/06316
摘要： Techniques for determining one or more disaster recovery (DR) service level agreements (SLAs) for each of one or more components of an application are provided. The techniques include identifying one or more components of an application, capturing one or more intra-application data dependencies between the one or more components, and mapping each of the one or more components to a DR profile to determine one or more DR SLAs for each of the one or more components of an application.
摘要翻译：提供了用于为应用的一个或多个组件中的每一个确定一个或多个灾难恢复（DR）服务水平协议（SLA）的技术。这些技术包括识别应用程序的一个或多个组件，捕获一个或多个组件之间的一个或多个应用程序内数据依赖关系，并将一个或多个组件中的每一个映射到DR配置文件，以确定每一个或多个组件的一个或多个DR SLA 的应用程序的一个或多个组件。

4. 发明授权

US09679029B2 Optimizing storage cloud environments through adaptive statistical modeling 有权
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.

5. 发明授权

US09329908B2 Proactive identification of hotspots in a cloud computing environment 有权
标题翻译：在云计算环境中主动识别热点
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。

6. 发明申请

US20120116743A1 OPTIMIZING STORAGE CLOUD ENVIRONMENTS THROUGH ADAPTIVE STATISTICAL MODELING 有权
标题翻译：通过自适应统计建模优化存储云环境
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。

7. 发明申请

US20120079097A1 PROACTIVE IDENTIFICATION OF HOTSPOTS IN A CLOUD COMPUTING ENVIRONMENT 有权
标题翻译：在云计算环境中对实体进行主动识别
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。

8. 发明授权

US08266280B2 System and method for a storage area network virtualization optimization 有权
标题翻译：用于存储区域网络虚拟化优化的系统和方法
公开(公告)号：US08266280B2
公开(公告)日：2012-09-11
申请号：US12725952
申请日：2010-03-17
申请人： Seshashayee S. Murthy , Ramani R. Routray , Sandeep M. Uttamchandani
发明人： Seshashayee S. Murthy , Ramani R. Routray , Sandeep M. Uttamchandani
IPC分类号： G06F15/173
CPC分类号： H04L63/10 , G06F3/0613 , G06F3/0635 , G06F3/067 , H04L67/1097 , H04L69/32
摘要： A method is implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions. The programming instructions are operable to determine one or more optimal mappings between a server layer and a storage layer through a network layer based on performance metrics of one or more ports of at least one of the server layer, the storage layer and the network layer.
摘要翻译：在具有计算机可执行代码的计算机基础设施中实现一种方法，其有形地体现在具有编程指令的计算机可读存储介质上编程指令可操作以基于服务器层，存储层和网络层中的至少一个的一个或多个端口的性能度量，通过网络层确定服务器层和存储层之间的一个或多个最优映射。

9. 发明申请

US20120271678A1 CHARGEBACK REDUCTION PLANNING FOR INFORMATION TECHNOLOGY MANAGEMENT 审中-公开
标题翻译：信息技术管理减免计划
公开(公告)号：US20120271678A1
公开(公告)日：2012-10-25
申请号：US13541440
申请日：2012-07-03
申请人： Sandip Agarwala , Ramani R. Routray , Sandeep M. Uttamchandani
发明人： Sandip Agarwala , Ramani R. Routray , Sandeep M. Uttamchandani
IPC分类号： G06Q10/06
CPC分类号： G06Q30/04 , G06Q10/06 , G06Q30/0283
摘要： Minimizing cost chargeback in an information technology (IT) computing environment including multiple resources. One implementation involves determining time-based usage patterns and allocation statistics for a plurality of resources and associated resource workloads. Using a regression function for determining a correlation of response time with resource usages and outstanding input/output instructions for the plurality of resources. Based on the time-based usage patterns, allocation statistics and the correlation, deriving an interpolation using positive and negative integrals to minimize a difference between allocated resource values and average allocation values. Determining service level objectives (SLOs) and resource allocation for minimizing cost chargeback for the resource workloads based on the derived interpolation.
摘要翻译：在包括多种资源在内的信息技术（IT）计算环境中最大限度地降低成本。一个实现涉及为多个资源和相关联的资源工作负载确定基于时间的使用模式和分配统计。使用回归函数来确定响应时间与资源使用的相关性以及用于多个资源的未完成的输入/输出指令。基于时间使用模式，分配统计和相关性，使用正负积分导出内插，以最小化分配的资源值与平均分配值之间的差异。确定服务水平目标（SLO）和资源分配，以根据导出的插值来最大限度地降低资源负担的成本。

10. 发明申请

US20110295815A1 Proactive Detection of Data Inconsistencies in a Storage System Point-in-Time Copy of Data 有权
标题翻译：主动检测存储系统中的数据不一致数据的时间点副本
公开(公告)号：US20110295815A1
公开(公告)日：2011-12-01
申请号：US12788026
申请日：2010-05-26
申请人： Nagapramod S. Mandagere , Ramani R. Routray , Sandeep M. Uttamchandani , Pin Zhou
发明人： Nagapramod S. Mandagere , Ramani R. Routray , Sandeep M. Uttamchandani , Pin Zhou
IPC分类号： G06F17/30
CPC分类号： G06F11/1004
摘要： Embodiments of the invention relate to testing a storage system point-in-time copy of data for consistency. An aspect of the invention includes receiving system and application event information from systems and applications associated with point-in-time copies of data. The system and application event information is associated with each of point-in-time copies of data. At least one point-in-time copy of data is selected for testing. The system and application event information is compared with inconsistency classes to determine tests for testing the point-in-time copy of data. The point-in-time copy of data is tested.
摘要翻译：本发明的实施例涉及测试用于一致性的数据的存储系统时间点副本。本发明的一个方面包括从与数据的时间点副本相关联的系统和应用接收系统和应用事件信息。系统和应用事件信息与数据的每个时间点副本相关联。选择至少一个时间点的数据副本进行测试。将系统和应用程序事件信息与不一致类进行比较，以确定测试数据的时间点副本。测试数据的时间点副本。

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