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1. 发明授权

US08996480B2 Method and apparatus for optimizing data storage 有权
标题翻译：用于优化数据存储的方法和装置
公开(公告)号：US08996480B2
公开(公告)日：2015-03-31
申请号：US13100323
申请日：2011-05-04
申请人： Sandip Agarwala , Luis Angel D. Bathen , Divyesh Jadav
发明人： Sandip Agarwala , Luis Angel D. Bathen , Divyesh Jadav
IPC分类号： G06F17/30 , G06F3/06
CPC分类号： G06F3/0608 , G06F3/061 , G06F3/064 , G06F3/0643 , G06F3/067 , G06F17/30153
摘要： Embodiments of the invention relate to evaluation and storage of data in a computer system configured with a shared pool of resources. A multi-level adaptive compression technique is employed to minimize the cost of data storage based upon the type of data being stored and their access pattern. The costs of data storage include capacity, bandwidth, and compute cycles. Data is transformed local to a client in communication with the shared pool, local to the shared pool, or as a combination with a partial transformation local to the client and a partial transformation local to the shared pool.
摘要翻译：本发明的实施例涉及在配置有共享资源池的计算机系统中的数据的评估和存储。采用多级自适应压缩技术，根据存储的数据类型及其访问模式，最小化数据存储的成本。数据存储的成本包括容量，带宽和计算周期。数据本地转换为与共享池通信的客户端，本地到共享池，或者与客户机本地部分变换的组合以及共享池本地的部分转换。

2. 发明申请

US20120284239A1 METHOD AND APPARATUS FOR OPTIMIZING DATA STORAGE 有权
标题翻译：用于优化数据存储的方法和装置
公开(公告)号：US20120284239A1
公开(公告)日：2012-11-08
申请号：US13100323
申请日：2011-05-04
申请人： Sandip Agarwala , Luis Angel D. Bathen , Divyesh Jadav
发明人： Sandip Agarwala , Luis Angel D. Bathen , Divyesh Jadav
IPC分类号： G06F17/30
CPC分类号： G06F3/0608 , G06F3/061 , G06F3/064 , G06F3/0643 , G06F3/067 , G06F17/30153
摘要： Embodiments of the invention relate to evaluation and storage of data in a computer system configured with a shared pool of resources. A multi-level adaptive compression technique is employed to minimize the cost of data storage based upon the type of data being stored and their access pattern. The costs of data storage include capacity, bandwidth, and compute cycles. Data is transformed local to a client in communication with the shared pool, local to the shared pool, or as a combination with a partial transformation local to the client and a partial transformation local to the shared pool.
摘要翻译：本发明的实施例涉及在配置有共享资源池的计算机系统中的数据的评估和存储。采用多级自适应压缩技术，根据存储的数据类型及其访问模式，最小化数据存储的成本。数据存储的成本包括容量，带宽和计算周期。数据本地转换为与共享池通信的客户端，本地到共享池，或者与客户机本地部分变换的组合以及共享池本地的部分转换。

3. 发明申请

US20120233310A1 COMPREHENSIVE BOTTLENECK DETECTION IN A MULTI-TIER ENTERPRISE STORAGE SYSTEM 失效
标题翻译：多层次企业存储系统中的综合检测
公开(公告)号：US20120233310A1
公开(公告)日：2012-09-13
申请号：US13044048
申请日：2011-03-09
申请人： Sandip Agarwala , David P. Goodman , Sandeep Gopisetty , David D. Weck
发明人： Sandip Agarwala , David P. Goodman , Sandeep Gopisetty , David D. Weck
IPC分类号： G06F15/173
CPC分类号： H04L47/11 , G06F9/5072 , G06F11/3442 , G06F11/3495 , H04L41/147 , H04L43/0882
摘要： Embodiments of the present invention provide approaches (e.g., online methods) to analyze end-to-end performance issues in a multi-tier enterprise storage system (ESS), such as a storage cloud, where data may be distributed across multiple storage components. Specifically, performance and configuration data from different storage components (e.g., nodes) is collected and analyzed to identify nodes that are becoming (or may become) performance bottlenecks. In a typical embodiment, a set of components distributed among a set of tiers of an ESS is identified. For each component, a total capacity and a current load are determined. Based on these values, a utilization of each component is determined. Comparison of the utilization with a predetermined threshold and/or analysis of historical data allows one or more components causing a bottleneck to be identified.
摘要翻译：本发明的实施例提供了分析多层企业存储系统（ESS）（诸如存储云）中的端到端性能问题的方法（例如在线方法），其中数据可以分布在多个存储组件上。具体地，收集和分析来自不同存储组件（例如，节点）的性能和配置数据以识别正在（或可能成为）性能瓶颈的节点。在典型的实施例中，识别分布在一组ESS中的一组分量。对于每个组件，确定总容量和当前负载。基于这些值，确定每个组件的利用率。将利用率与预定阈值进行比较和/或历史数据分析允许识别出瓶颈的一个或多个组件。

4. 发明申请

US20120047265A1 PERFORMANCE ISOLATION FOR STORAGE CLOUDS 有权
标题翻译：存储云的性能隔离
公开(公告)号：US20120047265A1
公开(公告)日：2012-02-23
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。

5. 发明申请

US20110238672A1 COST AND POWER EFFICIENT STORAGE AREA NETWORK PROVISIONING 有权
标题翻译：成本和功率有效的存储区域网络规定
公开(公告)号：US20110238672A1
公开(公告)日：2011-09-29
申请号：US12749435
申请日：2010-03-29
申请人： Sandip Agarwala , Harsha D. Gunatilaka , Ramani R. Routray
发明人： Sandip Agarwala , Harsha D. Gunatilaka , Ramani R. Routray
IPC分类号： G06F17/30
CPC分类号： H04L67/1097
摘要： Various embodiments for efficiently provisioning a storage area network (SAN) are provided. In one embodiment, SAN information is provided to an engine for optimization. The SAN information includes at least one of SAN configuration information, SAN usage information, at least one cost profile, and at least one chargeback model. Based on the SAN information, those of an available plurality of storage resources not meeting at least one storage criterion are filtered. The filtered storage resources are ranked on a cost basis. A resource configuration graph is constructed based on the ranked storage resources. The resource configuration graph is traversed to obtain a plurality of possible SAN configuration plans. At least one power profile is applied to the plurality of possible SAN configuration plans to rank the plurality of possible SAN configuration plans by energy consumption.
摘要翻译：提供了用于有效地配置存储区域网络（SAN）的各种实施例。在一个实施例中，SAN信息被提供给发动机以进行优化。 SAN信息包括SAN配置信息，SAN使用信息，至少一个成本简档和至少一个退款模型中的至少一个。基于SAN信息，过滤不符合至少一个存储标准的可用多个存储资源的SAN信息。过滤的存储资源按成本排列。基于排名的存储资源构建资源配置图。遍历资源配置图以获得多个可能的SAN配置计划。至少一个功率配置文件被应用于多个可能的SAN配置计划，以通过能量消耗对多个可能的SAN配置计划进行排序。

6. 发明授权

US09658892B2 Management of storage cluster performance with hybrid workloads 有权
公开(公告)号：US09658892B2
公开(公告)日：2017-05-23
申请号：US13222892
申请日：2011-08-31
申请人： Dean Hildebrand , Sandip Agarwala
发明人： Dean Hildebrand , Sandip Agarwala
IPC分类号： G06F9/50 , H04L12/801 , H04L12/851 , H04L12/911 , H04L29/08
CPC分类号： H04L47/76 , G06F9/50 , G06F9/505 , G06F9/5094 , H04L41/0896 , H04L47/10 , H04L47/24 , H04L47/78 , H04L67/10 , H04L67/1002 , H04L67/1095 , H04L67/1097 , H04L67/148 , H04L67/42
摘要： Embodiments of the invention relate to management of hybrid workloads, including serial and parallel workload optimizations, in a shared pool of configurable computer resources. Resource utilization in the shared pool is dynamically tracked, and employed for assessing a set of servers a parallel access protocol should utilize for one or more I/O requests in conjunction with any serial workload optimizations. Accordingly, the load balancing embodies a diverse set of workloads to support dynamic and equitable allocation.

7. 发明授权

US08515792B2 Method and system for chargeback allocation in information technology systems 有权
标题翻译：信息技术系统中的退款分配方法与系统
公开(公告)号：US08515792B2
公开(公告)日：2013-08-20
申请号：US12567538
申请日：2009-09-25
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： G06Q10/00
CPC分类号： G06Q40/02 , G06Q30/04 , G06Q40/12
摘要： The invention provides a system and method for chargeback cost allocation in an information technology (IT) system including multiple resources. The method includes categorizing cost attributes of different resources into multiple levels defining a cost attribute hierarchy, defining different chargeback groups for resources with similar cost attributes and chargeback policies at different levels of the hierarchy, and performing chargeback cost allocation by allocating the cost for resources at each hierarchy level independently using chargeback policies defined for the resources at that hierarchy level.
摘要翻译：本发明提供了一种包括多个资源的信息技术（IT）系统中的拒付成本分配的系统和方法。该方法包括将不同资源的成本属性划分成多个级别，定义成本属性层次，为具有相似成本属性的资源定义不同的拒付组，并且在不同级别的不同级别对退款策略进行定义，并通过分配资源成本来执行退款成本分配每个层次级别独立地使用为该层次级别的资源定义的退款策略。

8. 发明授权

US08407501B2 Allocation of storage resources in a networked computing environment based on energy utilization 有权
标题翻译：基于能源利用的网络计算环境中的存储资源分配
公开(公告)号：US08407501B2
公开(公告)日：2013-03-26
申请号：US13073081
申请日：2011-03-28
申请人： Sandip Agarwala , Eric K. Butler , Sandeep Gopisetty , Kavita Chavda
发明人： Sandip Agarwala , Eric K. Butler , Sandeep Gopisetty , Kavita Chavda
IPC分类号： G06F1/26
CPC分类号： H04L47/70 , G06F3/0625 , G06F3/0635 , G06F3/067 , Y02D10/154
摘要： Embodiments of the present invention provide an approach to provision storage resources (e.g., across an enterprise storage system (ESS) such as a general parallel file system (GPFS) or the like) for different workloads in an energy efficient manner. The system evaluates different energy profiles/workloads' energy consumption characteristics of storage devices to determine an allocation plan that reduces the energy cost (e.g., results in the lowest cost/energy consumption for handling a storage workload). In a typical embodiment, energy consumption characteristics for handling a particular storage workload will be determined. Thereafter, a type of storage device capable of handling the workload will be determined. Then, an allocation plan that results in the most efficient energy consumption for handling the workload will be developed. In general, the allocation plan is based upon the energy consumption characteristics and an energy efficiency algorithm. The energy efficiency algorithm serves to identify storage device(s) that can handle the workload in such a way as to reduce total energy consumption and, accordingly, costs. Along these lines, the energy efficiency algorithm may also consider other factors such as capacity and load of storage devices and service level agreement (SLA) terms in addition to energy costs (e.g., over times of day and/or days of week). In any event, at least one storage device can then be selected for handling the storage workload according to the allocation plan.
摘要翻译：本发明的实施例提供了一种以能量效率方式为不同工作负载提供存储资源（例如，跨企业存储系统（ESS），诸如通用并行文件系统（GPFS）等）的方法。该系统评估存储设备的不同能量简档/工作负载的能量消耗特征，以确定降低能量成本的分配计划（例如，导致用于处理存储工作负载的最低成本/能量消耗）。在典型的实施例中，将确定用于处理特定存储工作负载的能量消耗特性。此后，可以确定能够处理工作量的一种存储装置。然后，将开发出一种能够最有效地处理工作负载能耗的分配计划。一般来说，分配方案是基于能量消耗特性和能量效率算法。能源效率算法用于识别能够处理工作负载的存储设备，以减少总能量消耗，并因此降低成本。除此之外，能源效率算法还可以考虑其他因素，例如存储设备的容量和负载以及服务水平协议（SLA）术语以及能量成本（例如，超过一天和/或几周的时间）。在任何情况下，可以根据分配计划选择至少一个存储设备来处理存储工作负载。

9. 发明授权

US08306953B2 Online management of historical data for efficient reporting and analytics 有权
标题翻译：在线管理历史数据，以实现有效的报告和分析
公开(公告)号：US08306953B2
公开(公告)日：2012-11-06
申请号：US12872964
申请日：2010-08-31
申请人： Sandip Agarwala , Sandeep Gopisetty , Stefan Jaquet
发明人： Sandip Agarwala , Sandeep Gopisetty , Stefan Jaquet
IPC分类号： G06F7/00 , 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，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。

10. 发明申请

US20120254640A1 ALLOCATION OF STORAGE RESOURCES IN A NETWORKED COMPUTING ENVIRONMENT BASED ON ENERGY UTILIZATION 有权
标题翻译：基于能源利用的网络计算环境中的存储资源分配
公开(公告)号：US20120254640A1
公开(公告)日：2012-10-04
申请号：US13073081
申请日：2011-03-28
申请人： Sandip Agarwala , Eric K. Butler , Sandeep Gopisetty , Kavita Chavda
发明人： Sandip Agarwala , Eric K. Butler , Sandeep Gopisetty , Kavita Chavda
IPC分类号： G06F12/02 , G06F1/32
CPC分类号： H04L47/70 , G06F3/0625 , G06F3/0635 , G06F3/067 , Y02D10/154
摘要： Embodiments of the present invention provide an approach to provision storage resources (e.g., across an enterprise storage system (ESS) such as a general parallel file system (GPFS) or the like) for different workloads in an energy efficient manner. The system evaluates different energy profiles/workloads' energy consumption characteristics of storage devices to determine an allocation plan that reduces the energy cost (e.g., results in the lowest cost/energy consumption for handling a storage workload). In a typical embodiment, energy consumption characteristics for handling a particular storage workload will be determined. Thereafter, a type of storage device capable of handling the workload will be determined. Then, an allocation plan that results in the most efficient energy consumption for handling the workload will be developed. In general, the allocation plan is based upon the energy consumption characteristics and an energy efficiency algorithm. The energy efficiency algorithm serves to identify storage device(s) that can handle the workload in such a way as to reduce total energy consumption and, accordingly, costs. Along these lines, the energy efficiency algorithm may also consider other factors such as capacity and load of storage devices and service level agreement (SLA) terms in addition to energy costs (e.g., over times of day and/or days of week). In any event, at least one storage device can then be selected for handling the storage workload according to the allocation plan.
摘要翻译：本发明的实施例提供了一种以能量效率方式为不同工作负载提供存储资源（例如，跨企业存储系统（ESS），诸如通用并行文件系统（GPFS）等）的方法。该系统评估存储设备的不同能量简档/工作负载的能量消耗特征，以确定降低能量成本的分配计划（例如，导致用于处理存储工作负载的最低成本/能量消耗）。在典型的实施例中，将确定用于处理特定存储工作负载的能量消耗特性。此后，可以确定能够处理工作量的一种存储装置。然后，将开发出一种能够最有效地处理工作负载能耗的分配计划。一般来说，分配方案是基于能量消耗特性和能量效率算法。能源效率算法用于识别能够处理工作负载的存储设备，以减少总能量消耗，并因此降低成本。除此之外，能源效率算法还可以考虑其他因素，例如存储设备的容量和负载以及服务水平协议（SLA）术语以及能量成本（例如，超过一天和/或几周的时间）。在任何情况下，可以根据分配计划选择至少一个存储设备来处理存储工作负载。

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