会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明授权
    • Method and apparatus for utility-based dynamic resource allocation in a distributed computing system
    • 在分布式计算系统中基于实用程序的动态资源分配的方法和装置
    • US08352951B2
    • 2013-01-08
    • US12164896
    • 2008-06-30
    • Rajarshi DasJeffrey Owen KephartGerald James TesauroWilliam Edward Walsh
    • Rajarshi DasJeffrey Owen KephartGerald James TesauroWilliam Edward Walsh
    • G06F9/46G06F15/173
    • G06F9/5027G06F9/5083
    • In one embodiment, the present invention is a method for allocation of finite computational resources amongst multiple entities, wherein the method is structured to optimize the business value of an enterprise providing computational services. One embodiment of the inventive method involves establishing, for each entity, a service level utility indicative of how much business value is obtained for a given level of computational system performance. The service-level utility for each entity is transformed into a corresponding resource-level utility indicative of how much business value may be obtained for a given set or amount of resources allocated to the entity. The resource-level utilities for each entity are aggregated, and new resource allocations are determined and executed based upon the resource-level utility information. The invention is thereby capable of making rapid allocation decisions, according to time-varying need or value of the resources by each of the entities.
    • 在一个实施例中,本发明是一种用于在多个实体之间分配有限计算资源的方法,其中该方法被构造为优化提供计算服务的企业的商业价值。 本发明方法的一个实施例涉及为每个实体建立一个服务级别实用程序,其指示针对给定级别的计算系统性能获得多少商业价值。 每个实体的服务级别实用程序被转换成相应的资源级实用程序,指示可以为给定的集合或分配给该实体的资源量获得多少商业价值。 聚合每个实体的资源级实用程序,并根据资源级实用程序信息确定和执行新的资源分配。 因此,本发明能够根据每个实体的时间变化需要或资源价值进行快速分配决定。
    • 2. 发明申请
    • METHOD AND APPARATUS FOR UTILITY-BASED DYNAMIC RESOURCE ALLOCATION IN A DISTRIBUTED COMPUTING SYSTEM
    • 分布式计算系统中基于应用的动态资源分配的方法与装置
    • US20080263559A1
    • 2008-10-23
    • US12164896
    • 2008-06-30
    • RAJARSHI DASJeffrey Owen KephartGerald James TesauroWilliam Edward Walsh
    • RAJARSHI DASJeffrey Owen KephartGerald James TesauroWilliam Edward Walsh
    • G06F9/50
    • G06F9/5027G06F9/5083
    • In one embodiment, the present invention is a method for allocation of finite computational resources amongst multiple entities, wherein the method is structured to optimize the business value of an enterprise providing computational services. One embodiment of the inventive method involves establishing, for each entity, a service level utility indicative of how much business value is obtained for a given level of computational system performance. The service-level utility for each entity is transformed into a corresponding resource-level utility indicative of how much business value may be obtained for a given set or amount of resources allocated to the entity. The resource-level utilities for each entity are aggregated, and new resource allocations are determined and executed based upon the resource-level utility information. The invention is thereby capable of making rapid allocation decisions, according to time-varying need or value of the resources by each of the entities.
    • 在一个实施例中,本发明是一种用于在多个实体之间分配有限计算资源的方法,其中该方法被构造为优化提供计算服务的企业的商业价值。 本发明方法的一个实施例涉及为每个实体建立一个服务级别实用程序,其指示针对给定级别的计算系统性能获得多少商业价值。 每个实体的服务级别实用程序被转换成相应的资源级实用程序,指示可以为给定的集合或分配给该实体的资源量获得多少商业价值。 聚合每个实体的资源级实用程序,并根据资源级实用程序信息确定和执行新的资源分配。 因此,本发明能够根据每个实体的时间变化需要或资源价值进行快速分配决定。
    • 3. 发明授权
    • Method and apparatus for detecting a presence of a computer virus
    • 用于检测计算机病毒存在的方法和装置
    • US5907834A
    • 1999-05-25
    • US619866
    • 1996-03-18
    • Jeffrey Owen KephartGregory Bret SorkinGerald James TesauroSteven Richard White
    • Jeffrey Owen KephartGregory Bret SorkinGerald James TesauroSteven Richard White
    • G06F1/00G06F21/00G06F15/18G06F11/00
    • G06F21/564
    • A data string is a sequence of atomic units of data that represent information. In the context of computer data, examples of data strings include executable programs, data files, and boot records consisting of sequences of bytes, or text files consisting of sequences of bytes or characters. The invention solves the problem of automatically constructing a classifier of data strings, i.e., constructing a classifier which, given a string, determines which of two or more class labels should be assigned to it. From a set of (string, class-label) pairs, this invention provides an automated technique for extracting features of data strings that are relevant to the classification decision, and an automated technique for developing a classifier which uses those features to classify correctly the data strings in the original examples and, with high accuracy, classify correctly novel data strings not contained in the example set. The classifier is developed using "adaptive" or "learning" techniques from the domain of statistical regression and classification, such as, e.g., multi-layer neural networks. As an example, the technique can be applied to the task of distinguishing files or boot records that are infected by computer viruses from files or boot records that are not infected.
    • 数据串是表示信息的数据的原子单元的序列。 在计算机数据的上下文中,数据串的示例包括由字节序列组成的可执行程序,数据文件和引导记录,或由字节或字符序列组成的文本文件。 本发明解决了自动构建数据串分类器的问题,即,构建一个分类器,给定一个字符串,确定应该分配两个或多个类标签中的哪一个。 本发明从一组(串,类标签)对提供了一种用于提取与分类决定相关的数据串的特征的自动化技术,以及用于开发分类器的自动化技术,其使用这些特征来正确地分类数据 原始示例中的字符串,并且具有高精度,正确地分类示例集中未包含的新颖数据字符串。 分类器是使用“自适应”或“学习”技术从统计回归和分类领域开发的,例如多层神经网络。 例如,该技术可以应用于区分受计算机病毒感染的文件或引导记录的文件或未被感染的引导记录的任务。
    • 4. 发明授权
    • Adaptive statistical regression and classification of data strings, with
application to the generic detection of computer viruses
    • 数据串的自适应统计回归和分类,应用于计算机病毒的通用检测
    • US5675711A
    • 1997-10-07
    • US242757
    • 1994-05-13
    • Jeffrey Owen KephartGregory Bret SorkinGerald James TesauroSteven Richard White
    • Jeffrey Owen KephartGregory Bret SorkinGerald James TesauroSteven Richard White
    • G06F1/00G06F21/00G06E1/00G06F15/18
    • G06F21/564
    • A data string is a sequence of atomic units of data that represent information. In the context of computer data, examples of data strings include executable programs, data files, and boot records consisting of sequences of bytes, or text files consisting of sequences of bytes or characters. The invention solves the problem of automatically constructing a classifier of data strings, i.e., constructing a classifier which, given a string, determines which of two or more class labels should be assigned to it. From a set of (string, class-label) pairs, this invention provides an automated technique for extracting features of data strings that are relevant to the classification decision, and an automated technique for developing a classifier which uses those features to classify correctly the data strings in the original examples and, with high accuracy, classify correctly novel data strings not contained in the example set. The classifier is developed using "adaptive" or "learning" techniques from the domain of statistical regression and classification, such as, e.g., multi-layer neural networks. As an example, the technique can be applied to the task of distinguishing files or boot records that are infected by computer viruses from files or boot records that are not infected.
    • 数据串是表示信息的数据的原子单元的序列。 在计算机数据的上下文中,数据串的示例包括由字节序列组成的可执行程序,数据文件和引导记录,或由字节或字符序列组成的文本文件。 本发明解决了自动构建数据串分类器的问题,即,构建一个分类器,给定一个字符串,确定应该分配两个或多个类标签中的哪一个。 本发明从一组(串,类标签)对提供了一种用于提取与分类决定相关的数据串的特征的自动化技术,以及用于开发分类器的自动化技术,其使用这些特征来正确地分类数据 原始示例中的字符串,并且具有高精度,正确地分类示例集中未包含的新颖数据字符串。 分类器是使用“自适应”或“学习”技术从统计回归和分类领域开发的,例如多层神经网络。 例如,该技术可以应用于区分受计算机病毒感染的文件或引导记录的文件或未被感染的引导记录的任务。