System and method for generic automated tuning for performance management
    2.
    发明授权
    System and method for generic automated tuning for performance management 有权
    用于性能管理的通用自动调整的系统和方法

    公开(公告)号:US06718358B1

    公开(公告)日:2004-04-06

    申请号:US09541368

    申请日:2000-03-31

    IPC分类号: G06F900

    CPC分类号: G06F9/5061

    摘要: A system and method is described for generic automated tuning for performance management. The system comprises a target to be controlled and a generic automated tuning agent (GATA) that performs this control. The controlled target provides interfaces to metrics relating to workload, service levels, and configuration information, as well as a means to adjust tuning controls that determine resource allocations within the target. The GATA inputs the metrics, estimates new tuning control settings based on service objectives specified by administrators, and outputs the tuning control settings.

    摘要翻译: 描述了用于性能管理的通用自动调整的系统和方法。 该系统包括要控制的目标和执行该控制的通用自动调整代理(GATA)。 受控目标提供与工作负载,服务级别和配置信息相关的指标的接口,以及调整确定目标内资源分配的调整控制的方法。 GATA输入指标,根据管理员指定的服务目标估计新的调整控制设置,并输出调谐控制设置。

    Method and system for recognizing end-user transactions
    3.
    发明授权
    Method and system for recognizing end-user transactions 失效
    用于识别最终用户交易的方法和系统

    公开(公告)号:US06925452B1

    公开(公告)日:2005-08-02

    申请号:US09575553

    申请日:2000-05-22

    CPC分类号: G06N99/005

    摘要: A method and system are described for end-user transaction recognition based on server data such as sequences of remote procedure calls (RPCs). The method may comprise machine-learning techniques for pattern recognition such as Bayesian classification, feature extraction mechanisms, and a dynamic-programming approach to segmentation of RPC sequences. The method preferably combines information-theoretic and machine-learning approaches. The system preferably includes a learning engine and an operation engine. A learning engine may comprise a data preparation subsystem (feature extraction) and a Bayes Net learning subsystem (model construction). The operation engine may comprise transaction segmentation and transaction classification subsystems.

    摘要翻译: 基于诸如远程过程调用序列(RPC)的服务器数据描述用于最终用户事务识别的方法和系统。 该方法可以包括用于模式识别的机器学习技术,例如贝叶斯分类,特征提取机制和用于RPC序列分割的动态规划方法。 该方法优选地结合了信息理论和机器学习方法。 该系统优选地包括学习引擎和操作引擎。 学习引擎可以包括数据准备子系统(特征提取)和贝叶斯网络学习子系统(模型构造)。 操作引擎可以包括事务分段和事务分类子系统。

    Method and system for embedding correlated performance measurements for distributed application performance decomposition
    4.
    发明授权
    Method and system for embedding correlated performance measurements for distributed application performance decomposition 失效
    用于嵌入分布式应用程序性能分解的相关性能测量的方法和系统

    公开(公告)号:US07720958B2

    公开(公告)日:2010-05-18

    申请号:US09875722

    申请日:2001-06-06

    IPC分类号: G06F15/173

    摘要: Techniques for use in accordance with application performance decomposition are provided which take advantage of the communications protocol used to carry a transaction between application components in a distributed computing network. Specifically, the invention extends the communications protocol by embedding data, such as timestamp and duration measurement data, in the protocol itself, rather than extending or altering the application or transaction data carried by the protocol as in existing approaches. Thus, the invention provides natural correlation of interactions of distributed application components on such transactions without modification to the application or transaction data. Because the correlation is performed in-line with the application component interactions, minimal data management overhead is required, and correlated performance decomposition is made possible in real-time for the transaction. Furthermore, subsequent processing stages of the distributed application can interpret the communications protocol to glean processing durations of previous stages in order to make decisions regarding treatment of the transaction.

    摘要翻译: 提供了根据应用性能分解使用的技术,其利用用于在分布式计算网络中的应用组件之间进行事务的通信协议。 具体地,本发明通过在协议本身中嵌入诸如时间戳和持续时间测量数据的数据来扩展通信协议,而不是如现有方法那样扩展或改变由协议携带的应用或交易数据。 因此,本发明提供了分布式应用组件在这种交易上的交互的自然相关性,而不需要修改应用或交易数据。 由于相关性是与应用程序组件交互进行的,所以需要最小的数据管理开销,并且可以实时地进行相关性能分解。 此外,分布式应用的后续处理阶段可以解释通信协议以收集先前阶段的处理持续时间,以便做出关于交易处理的决定。

    Method, computer program product, and system for deriving web transaction performance metrics
    5.
    发明授权
    Method, computer program product, and system for deriving web transaction performance metrics 有权
    方法,计算机程序产品和用于导出Web事务性能指标的系统

    公开(公告)号:US06701363B1

    公开(公告)日:2004-03-02

    申请号:US09516172

    申请日:2000-02-29

    IPC分类号: G06F15173

    摘要: The present invention comprises a method of relating characteristics gleaned by monitoring application transaction flows (and the decomposition thereof) to produce performance metrics useful to characterize the efficiency and performance of web transactions used in a web-based application. These metrics can assist application designers and developers in reorganizing their application content, programs, and transports to provide improved service to their consumer. Events are generated and composed into predefined activities on a web transaction basis. The performance metric is then derived that entails a relationship between at least two different activities that gives insight into the performance characteristics of the web transaction. By using the derived performance metrics, designers and developers of web pages can judge the effects of changes to their application relative to efficiency and performance. Different applications can also be compared and contrasted using these metrics. Furthermore, these metrics may serve as inputs to planning models used to project capacity, throughput, response time, and availability of the application.

    摘要翻译: 本发明包括一种通过监视应用事务流(及其分解)来收集特征的方法,以产生用于表征在基于Web的应用中使用的网络交易的效率和性能的性能度量。 这些指标可以帮助应用程序设计人员和开发人员重组其应用程序内容,程序和传输,以便为其消费者提供改进的服务。 生成事件,并将其组织成基于Web事务的预定义活动。 然后导出性能度量,其包含至少两个不同活动之间的关系,这些活动可以深入了解Web事务的性能特征。 通过使用派生的性能指标,网页的设计人员和开发人员可以相对于效率和性能来判断其应用程序的更改的影响。 也可以使用这些度量来比较和对比不同的应用程序。 此外,这些指标可以作为用于计划应用程序的容量,吞吐量,响应时间和可用性的规划模型的输入。

    METHOD AND APPARATUS FOR ONLINE SAMPLE INTERVAL DETERMINATION
    7.
    发明申请
    METHOD AND APPARATUS FOR ONLINE SAMPLE INTERVAL DETERMINATION 失效
    在线样品间隔测定的方法和装置

    公开(公告)号:US20080263563A1

    公开(公告)日:2008-10-23

    申请号:US12165009

    申请日:2008-06-30

    IPC分类号: G06F9/50

    摘要: In one embodiment, functional system elements are added to an autonomic manager to enable automatic online sample interval selection. In another embodiment, a method for determining the sample interval by continually characterizing the system workload behavior includes monitoring the system data and analyzing the degree to which the workload is stationary. This makes the online optimization method less sensitive to system noise and capable of being adapted to handle different workloads. The effectiveness of the autonomic optimizer is thereby improved, making it easier to manage a wide range of systems.

    摘要翻译: 在一个实施例中,将功能系统元件添加到自主管理器以启用自动在线采样间隔选择。 在另一个实施例中,用于通过连续地表征系统工作负载行为来确定采样间隔的方法包括监视系统数据并分析工作负载静止的程度。 这使得在线优化方法对系统噪声不太敏感,并且能够适应于处理不同的工作负载。 从而改进了自主优化器的有效性,从而更容易地管理广泛的系统。

    Methods and apparatus for performing adaptive and robust prediction
    8.
    发明授权
    Methods and apparatus for performing adaptive and robust prediction 失效
    用于执行自适应和鲁棒预测的方法和装置

    公开(公告)号:US07039559B2

    公开(公告)日:2006-05-02

    申请号:US10385265

    申请日:2003-03-10

    IPC分类号: G06F3/05

    CPC分类号: G06F9/5083 G06F2209/5019

    摘要: Techniques for performing adaptive and robust prediction. Prediction techniques are adaptive in that they use a minimal amount of historical data to make predictions, the amount of data being selectable. The techniques are able to learn quickly about changes in the workload traffic pattern and make predictions, based on such learning, that are useful for proactive response to workload changes. To counter the increased variability in the prediction as a result of using minimal history, robustness is improved by checking model stability at every time interval and revising the model structure as needed to meet designated stability criteria. Furthermore, the short term prediction techniques can be used in conjunction with a long term forecaster.

    摘要翻译: 用于执行自适应和鲁棒预测的技术。 预测技术是自适应的,因为它们使用最少量的历史数据进行预测,数据量可选择。 这些技术能够快速了解​​工作负载流量模式的变化,并根据此类学习进行预测,对于对工作负载变化的主动响应非常有用。 为了应对由于使用最小历史而导致的预测增加的变异性,通过在每个时间间隔检查模型稳定性并根据需要修改模型结构来改善鲁棒性以满足指定的稳定性标准。 此外,短期预测技术可以与长期预报员结合使用。

    Systems and methods for service and role-based software distribution

    公开(公告)号:US07013461B2

    公开(公告)日:2006-03-14

    申请号:US09755786

    申请日:2001-01-05

    CPC分类号: G06F8/61

    摘要: Computer-based methods and systems for performing automated distribution of a software package to one or more target machines in one or more regions of a distributed network of target machines, comprises the following steps. First, a base software package is prepared for each of the one or more regions based on at least one of: (i) policy data indicating which of the one or more regions are candidates for receiving the software package, (ii) dependency information indicating requisites for a service provided by the software package, and (iii) configuration information for each of the candidate regions. The base software package is then distributed to each of the candidate regions of the distributed network. The base software package received at each of the candidate regions is then customized based on at least one of: (i) regional distribution policies, (ii) dependency information specific to one or more roles performed by the target machines in that region, and (iii) individual target machine configuration information. Lastly, the software package customized in each of the candidate regions is distributed to at least one of the target machines in the candidate regions of the distributed network.

    System and method for on-line adaptive prediction using dynamic management of multiple sub-models
    10.
    发明授权
    System and method for on-line adaptive prediction using dynamic management of multiple sub-models 失效
    使用多个子模型的动态管理进行在线自适应预测的系统和方法

    公开(公告)号:US06937966B1

    公开(公告)日:2005-08-30

    申请号:US09591122

    申请日:2000-06-09

    IPC分类号: G06Q10/06 G06F7/60

    CPC分类号: G06Q10/06

    摘要: Predictive models are widely used for tasks in many domains. The present invention addresses the problem of prediction of non-stationary processes by dynamically managing multiple models. The system comprises a model assessor, a model adapter, a plurality of sub-models, a plurality of model combiner functions, training data that is used to estimate model parameters, and test data that is used to test for change points. Two processes are described, one for handling data updates and another that addresses prediction requests.

    摘要翻译: 预测模型广泛用于许多领域的任务。 本发明通过动态管理多个模型来解决非平稳过程的预测问题。 该系统包括模型评估者,模型适配器,多个子模型,多个模型组合器功能,用于估计模型参数的训练数据,以及用于测试变化点的测试数据。 描述两个处理过程,一个用于处理数据更新,另一个处理预测请求。