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    • 3. 发明申请
    • Automated diagnosis and forecasting of service level objective states
    • 服务水平目标状态的自动诊断和预测
    • US20060188011A1
    • 2006-08-24
    • US10987611
    • 2004-11-12
    • Moises GoldszmidtIra CohenTerence KellyJulie Symons
    • Moises GoldszmidtIra CohenTerence KellyJulie Symons
    • H03H7/30
    • G06Q10/04
    • Systems, methods, and software used in performing automated diagnosis and identification of or forecasting service level object states. Some embodiments include building classifier models based on collected metric data to detect and forecast service level objective (SLO) violations. Some such systems, methods, and software further include automated detecting and forecasting of SLO violations along with providing alarms, messages, or commands to administrators or system components. Some such messages include diagnostic information with regard to a cause of a SLO violation. Some embodiments further include storing data representative of system performance and detected and forecast system SLO states. This data can then be used to generate reports of system performance including representations of system SLO states.
    • 用于执行自动诊断和识别或预测服务级对象状态的系统,方法和软件。 一些实施例包括基于收集的度量数据建立分类器模型以检测和预测服务水平目标(SLO)违规。 一些这样的系统,方法和软件还包括自动检测和预测SLO违规以及向管理员或系统组件提供警报,消息或命令。 一些这样的消息包括关于SLO违规的原因的诊断信息。 一些实施例还包括存储表示系统性能的数据和检测和预测系统SLO状态。 然后,该数据可用于生成系统性能的报告,包括系统SLO状态的表示。
    • 6. 发明授权
    • Determining and annotating a signature of a computer resource
    • 确定和注释计算机资源的签名
    • US07184935B1
    • 2007-02-27
    • US11149566
    • 2005-06-10
    • Ira CohenMoises Goldszmidt
    • Ira CohenMoises Goldszmidt
    • G06F3/01
    • G06F11/3409G06F11/3452G06F11/3466G06F2201/81G06F2201/875
    • Metrics for a computer resource are collected. A signature representing a state of the computer resource from the metrics are determined by determining raw values for each of the metrics and generating a vector from at least some of the raw values for the metrics, where generating the vector further comprises generating models for possible system states of the computer resource, determining a model that closely matches a state of the computer resource, determining key metrics for the model, and determining a vector of values from the key metrics. An annotation that describes the state of the computer resource is received and associated with the signature. The signature and the associated annotation are stored such that they are searchable.
    • 收集计算机资源的指标。 通过确定每个度量的原始值并从用于度量的至少一些原始值生成向量来确定表示来自度量的计算机资源的状态的签名,其中生成向量还包括为可能的系统生成模型 计算机资源的状态,确定与计算机资源的状态紧密匹配的模型,确定模型的关键度量,以及根据关键度量确定值向量。 描述计算机资源的状态的注释被接收并与签名相关联。 存储签名和相关注释,使其可搜索。
    • 9. 发明授权
    • Automated identification of performance crisis
    • 自动识别性能危机
    • US08078913B2
    • 2011-12-13
    • US12473900
    • 2009-05-28
    • Moises GoldszmidtPeter Bodik
    • Moises GoldszmidtPeter Bodik
    • G06F11/00
    • G06F11/079G06F11/0709G06F11/3409G06F2201/81H04L41/0681
    • Methods for automatically identifying and classifying a crisis state occurring in a system having a plurality of computer resources. Signals are received from a device that collects the signals from each computer resource in the system. For each epoch, an epoch fingerprint is generated. Upon detecting a performance crisis within the system, a crisis fingerprint is generated consisting of at least one epoch fingerprint. The technology is able to identify that a performance crisis has previously occurred within the datacenter if a generated crisis fingerprint favorably matches any of the model crisis fingerprints stored in a database. The technology may also predict that a crisis is about to occur.
    • 用于自动识别和分类在具有多个计算机资源的系统中发生的危机状态的方法。 从收集系统中每台计算机资源的信号的设备接收信号。 对于每个时期,都会产生一个时代指纹。 在检测到系统内的性能危机之后,产生由至少一个时代指纹组成的危机指纹。 该技术能够确定如果生成的危机指纹有利地匹配存储在数据库中的任何模型危机指纹,则数据中心之前发生了性能危机。 该技术还可能预测危机即将发生。
    • 10. 发明申请
    • TIME MODULATED GENERATIVE PROBABILISTIC MODELS FOR AUTOMATED CAUSAL DISCOVERY
    • 用于自动发现的时间调制生成概率模型
    • US20090144034A1
    • 2009-06-04
    • US11949061
    • 2007-12-03
    • Aleksandr SimmaMoises Goldszmidt
    • Aleksandr SimmaMoises Goldszmidt
    • G06F17/10G06G7/62
    • H04L41/0663H04L41/142H04L41/145
    • Dependencies between different channels or different services in a client or server may be determined from the observation of the times of the incoming and outgoing of the packets constituting those channels or services. A probabilistic model may be used to formally characterize these dependencies. The probabilistic model may be used to list the dependencies between input packets and output packets of various channels or services, and may be used to establish the expected strength of the causal relationship between the different events surrounding those channels or services. Parameters of the probabilistic model may be either based on prior knowledge, or may be fit using statistical techniques based on observations about the times of the events of interest. Expected times of occurrence between events may be observed, and dependencies may be determined in accordance with the probabilistic model.
    • 客户端或服务器中的不同信道或不同业务之间的依赖关系可以从对构成这些信道或业务的分组的进入和传出的时间的观察来确定。 概率模型可用于正式表征这些依赖性。 概率模型可以用于列出输入分组和各种信道或服务的输出分组之间的依赖性,并且可以用于建立围绕这些信道或服务的不同事件之间的因果关系的预期强度。 概率模型的参数可以基于现有知识,或者可以使用基于关于感兴趣事件的时间的观察的统计技术来拟合。 可以观察事件之间的预期发生时间,并且依赖性可以根据概率模型来确定。