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    • 1. 发明授权
    • Storage environment with symmetric frontend and asymmetric backend
    • 具有对称前端和非对称后端的存储环境
    • US08924656B1
    • 2014-12-30
    • US13456654
    • 2012-04-26
    • Ameya Prakash UsgaonkarParag DeshmukhSiddhartha NandiBipul Raj
    • Ameya Prakash UsgaonkarParag DeshmukhSiddhartha NandiBipul Raj
    • G06F12/00
    • G06F3/067G06F3/0614G06F3/0659G06F11/2092G06F11/2097
    • One or more techniques and/or systems are provided for configuring a storage environment. In particular, the storage environment may be configured with a symmetric frontend and an asymmetric backend. That is, an owner storage controller may be granted read/write access to a storage device owned by the owner storage controller, while a non-owner storage controller may be granted merely read access. In this way, the owner storage controller may execute, log, and/or commit a write command to the storage device, while the non-owner storage controller may merely execute, but not log and/or commit, a write command. Write buffers, log memories, and/or file system metadata may be synchronized between the owner storage controller and the non-owner storage controller, such that the non-owner storage controller may efficiently take ownership of the storage device in response to a failure of the owner storage controller.
    • 提供一个或多个技术和/或系统用于配置存储环境。 特别地,存储环境可以配置有对称前端和不对称后端。 也就是说,所有者存储控制器可以被授予对所有者存储控制器拥有的存储设备的读/写访问,而非所有者存储控制器可以被授予只读访问权限。 以这种方式,所有者存储控制器可以对存储设备执行,记录和/或提交写入命令,而非所有者存储控制器可以仅执行但不记录和/或提交写入命令。 写入缓冲器,日志存储器和/或文件系统元数据可以在所有者存储控制器和非所有者存储控制器之间同步,使得非所有者存储控制器可以有效地取得存储设备的所有权以响应于 所有者存储控制器。
    • 10. 发明授权
    • Modeling storage system performance
    • 建模存储系统性能
    • US09514022B1
    • 2016-12-06
    • US13275607
    • 2011-10-18
    • Jayanta BasakKaladhar VorugantiSiddhartha Nandi
    • Jayanta BasakKaladhar VorugantiSiddhartha Nandi
    • G06F11/34
    • G06F11/3447G06F11/00
    • A system and method for creating an accurate black-box model of a live storage system and for predicting performance of the storage system under a given workload is disclosed. An analytics engine determines a subset of counters that are relevant to performance of the storage system with respect to a particular output (e.g., throughput or latency) from performance data in counters of the storage system. Using the subset of counters, the analytics engine creates a workload signature for the storage system by using a recursive partitioning technique, such as a classification and regression tree. The analytics engine then creates the black-box model of the storage system performance by applying uncertainty measurement techniques, such as a Gaussian process, to the workload signature.
    • 公开了一种用于创建实时存储系统的精确黑箱模型并用于在给定工作负载下预测存储系统的性能的系统和方法。 分析引擎确定与存储系统的计数器中的性能数据相关的特定输出(例如,吞吐量或延迟)与存储系统的性能相关的计数器的子集。 使用计数器子集,分析引擎通过使用递归分区技术(如分类和回归树)为存储系统创建工作负载签名。 然后,分析引擎通过对工作负载签名应用不确定性测量技术(例如高斯过程)来创建存储系统性能的黑盒模型。