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1. 发明申请

US20120117160A1 ADAPTIVE DIFFERENTIAL PROPAGATION OF SOAP MESSAGES 有权
标题翻译： SOAP消息的自适应差分传播
公开(公告)号：US20120117160A1
公开(公告)日：2012-05-10
申请号：US12942042
申请日：2010-11-09
申请人： Danny Bickson , Han Chen , Gidon Gershinsky , Konstantin Shagin
发明人： Danny Bickson , Han Chen , Gidon Gershinsky , Konstantin Shagin
IPC分类号： G06F15/16
CPC分类号： H04L67/02
摘要： A method of adaptive differential propagation of Simple Object Access Protocol (SOAP) messages is provided herein. The method includes the following stages: classifying incoming SOAP messages according to at least one of: structure, content, and context thereof; selecting a corresponding template out of a plurality of templates for each classified SOAP message such that the selected template minimized a specified diff function applied to the classified SOAP message and the selected template; applying the specified diff function to the SOAP message and the selected template to yield a respective delta; and encapsulating a template identifier with the respective delta, wherein the template identifier is uniquely associated with the selected template, to yield an outgoing SOAP message.
摘要翻译：本文提供了简单对象访问协议（SOAP）消息的自适应差分传播的方法。该方法包括以下阶段：根据以下至少一个对传入的SOAP消息进行分类：结构，内容和上下文; 为每个分类的SOAP消息从多个模板中选择相应的模板，使得所选择的模板最小化应用于分类的SOAP消息和所选模板的指定的差异功能; 将指定的差分函数应用于SOAP消息和所选择的模板以产生相应的增量; 以及用相应的增量来封装模板标识符，其中所述模板标识符与所选择的模板唯一地相关联，以产生传出的SOAP消息。

2. 发明授权

US08139656B2 Method and system for linear processing of an input using Gaussian belief propagation 有权
标题翻译：使用高斯置信传播对输入进行线性处理的方法和系统
公开(公告)号：US08139656B2
公开(公告)日：2012-03-20
申请号：US12238197
申请日：2008-09-25
申请人： Ori Shental , Danny Dolev , Danny Bickson
发明人： Ori Shental , Danny Dolev , Danny Bickson
IPC分类号： H04L27/00
CPC分类号： G06N7/005 , G06F17/12 , H04L25/03987
摘要： Methods and systems for processing an input. An input vector y is received that represents a noisy observation of Ax, where A is a data matrix and x is a data vector of unknown variables. Data vector x is recovered from the received input vector y via an iterative method. The recovering comprises determining an inference of a vector of marginal means over a graph G, where the graph G is of a joint Gaussian probability density function p(x) associated with noise in the received input vector y.
摘要翻译：用于处理输入的方法和系统。接收表示Ax的噪声观察的输入向量y，其中A是数据矩阵，x是未知变量的数据向量。通过迭代方法从接收的输入向量y中恢复数据向量x。恢复包括在图G上确定边际装置的向量的推论，其中图G是与接收的输入向量y中的噪声相关联的联合高斯概率密度函数p（x）。

3. 发明申请

US20110078291A1 DISTRIBUTED PERFORMANCE MONITORING IN SOFT REAL-TIME DISTRIBUTED SYSTEMS 审中-公开
标题翻译：在软实时分布式系统中进行分布式性能监控
公开(公告)号：US20110078291A1
公开(公告)日：2011-03-31
申请号：US12569954
申请日：2009-09-30
申请人： Danny Bickson , Gidon Gershinsky , Konstantin Shagin
发明人： Danny Bickson , Gidon Gershinsky , Konstantin Shagin
IPC分类号： G06F15/173 , G06F15/177
CPC分类号： G06F11/3409 , G06F11/3452 , G06F2201/805 , G06F2201/875
摘要： A novel and useful framework, system and method of monitoring one or more performance parameters (e.g., distributed system performance), filtering the performance parameters data collected and identifying one or more performance parameters that affect one or more target performance measures. This can be achieved in the case of a delay parameter, for example, by determining the root-cause of the increased delay and taking corrective actions in order to avoid violation of the timeliness constraints. The present invention is a statistical based performance monitoring mechanism that uses statistical signal processing techniques and is applicable, for example, in soft real-time distributed systems. The monitoring framework efficiently and distributively characterizes the behavior of the varying network conditions as a stochastic process and performs root-cause analysis to detecting the parameters which affect one or more target performance measures, e.g., latency. Once the affecting parameters are determined, corrective action is optionally taken.
摘要翻译：监测一个或多个性能参数（例如，分布式系统性能）的新颖有用的框架，系统和方法，过滤所收集的性能参数数据并识别影响一个或多个目标性能测量的一个或多个性能参数。这可以在延迟参数的情况下实现，例如通过确定增加的延迟的根本原因并采取校正动作，以避免违反时效性约束。本发明是基于统计的性能监视机制，其使用统计信号处理技术，并且可应用于例如软实时分布式系统。监控框架有效地并且分布地将不同网络条件的行为特征化为随机过程，并执行根本原因分析以检测影响一个或多个目标性能测量（例如等待时间）的参数。一旦确定了影响的参数，则可以采取校正动作。

4. 发明授权

US08621016B2 Adaptive differential propagation of soap messages 有权
标题翻译：肥皂消息的自适应差分传播
公开(公告)号：US08621016B2
公开(公告)日：2013-12-31
申请号：US12942042
申请日：2010-11-09
申请人： Danny Bickson , Han Chen , Gidon Gershinsky , Konstantin Shagin
发明人： Danny Bickson , Han Chen , Gidon Gershinsky , Konstantin Shagin
IPC分类号： G06F15/16
CPC分类号： H04L67/02
摘要： A method of adaptive differential propagation of Simple Object Access Protocol (SOAP) messages is provided herein. The method includes the following stages: classifying incoming SOAP messages according to at least one of: structure, content, and context thereof; selecting a corresponding template out of a plurality of templates for each classified SOAP message such that the selected template minimized a specified diff function applied to the classified SOAP message and the selected template; applying the specified diff function to the SOAP message and the selected template to yield a respective delta; and encapsulating a template identifier with the respective delta, wherein the template identifier is uniquely associated with the selected template, to yield an outgoing SOAP message.
摘要翻译：本文提供了简单对象访问协议（SOAP）消息的自适应差分传播的方法。该方法包括以下阶段：根据以下至少一个对传入的SOAP消息进行分类：结构，内容和上下文; 为每个分类的SOAP消息从多个模板中选择相应的模板，使得所选择的模板最小化应用于分类的SOAP消息和所选模板的指定的差异功能; 将指定的差分函数应用于SOAP消息和所选择的模板以产生相应的增量; 以及用相应的增量来封装模板标识符，其中所述模板标识符与所选择的模板唯一地相关联，以产生传出的SOAP消息。

5. 发明申请

US20100074342A1 Method and system for linear processing of an input using Gaussian Belief Propagation 有权
标题翻译：使用高斯信念传播进行线性处理的方法和系统
公开(公告)号：US20100074342A1
公开(公告)日：2010-03-25
申请号：US12238197
申请日：2008-09-25
申请人： Ori Shental , Danny Dolev , Danny Bickson
发明人： Ori Shental , Danny Dolev , Danny Bickson
IPC分类号： H04L27/00 , G06N5/02
CPC分类号： G06N7/005 , G06F17/12 , H04L25/03987
摘要： Methods and systems for processing an input. An input vector y is received that represents a noisy observation of Ax, where A is a data matrix and x is a data vector of unknown variables. Data vector x is recovered from the received input vector y via an iterative method. The recovering comprises determining an inference of a vector of marginal means over a graph G, where the graph G is of a joint Gaussian probability density function p(x) associated with noise in the received input vector y.
摘要翻译：用于处理输入的方法和系统。接收表示Ax的噪声观察的输入向量y，其中A是数据矩阵，x是未知变量的数据向量。通过迭代方法从接收的输入向量y中恢复数据向量x。恢复包括在图G上确定边际装置的向量的推论，其中图G是与接收的输入向量y中的噪声相关联的联合高斯概率密度函数p（x）。

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