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公开(公告)号：US20090161570A1
公开(公告)日：2009-06-25
申请号：US12272712
申请日：2008-11-17
IPC分类号： H04L12/26
CPC分类号： H04L12/14 , H04L12/1428 , H04L41/0896 , H04L41/5009 , H04L43/022 , H04L43/024 , H04L43/026 , H04L43/16 , H04L63/1408 , Y02D50/30
摘要： Two regularized estimators that avoid the pathologies associated with variance estimation are disclosed. The regularized variance estimator adds a contribution to estimated variance representing the likely error, and hence ameliorates the pathologies of estimating small variances while at the same time allowing more reliable estimates to be balanced in the convex combination estimator. The bounded variance estimator employs an upper bound to the variance which avoids estimation pathologies when sampling probabilities are very small.
摘要翻译： 公开了避免与方差估计相关的病理学的两个正则化估计。 正则化方差估计器对代表可能误差的估计方差增加了一个贡献，从而改善了估计小变异的病态，同时允许在凸组合估计中平衡更可靠的估计。 有界方差估计器采用方差的上限，避免了当抽样概率非常小时的估计病变。
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公开(公告)号：US07536455B2
公开(公告)日：2009-05-19
申请号：US11488874
申请日：2006-07-18
IPC分类号： G06F15/16
CPC分类号： H04L12/14 , H04L12/1428 , H04L41/0896 , H04L41/5009 , H04L43/022 , H04L43/024 , H04L43/026 , H04L43/16 , H04L63/1408 , Y02D50/30
摘要： Two regularized estimators that avoid the pathologies associated with variance estimation are disclosed. The regularized variance estimator adds a contribution to estimated variance representing the likely error, and hence ameliorates the pathologies of estimating small variances while at the same time allowing more reliable estimates to be balanced in the convex combination estimator. The bounded variance estimator employs an upper bound to the variance which avoids estimation pathologies when sampling probabilities are very small.
摘要翻译： 公开了避免与方差估计相关的病理学的两个正则化估计。 正则化方差估计器对代表可能误差的估计方差增加了一个贡献，从而改善了估计小变异的病态，同时允许在凸组合估计中平衡更可靠的估计。 有界方差估计器采用方差的上限，避免了当抽样概率非常小时的估计病变。
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公开(公告)号：US07299283B1
公开(公告)日：2007-11-20
申请号：US11478960
申请日：2006-06-27
IPC分类号： G06F15/16
CPC分类号： H04L43/00 , H04L12/14 , H04L41/0896 , H04L41/5009 , H04L43/024 , H04L43/026 , H04L43/028 , H04L43/16
摘要： The present invention provides apparatus for sampling data flows in a data network in order to estimate a total data volume in the network. Sampling the data flows in the data network reduces the network resources that must be expended by the network to support the associated activity. The present invention enables the service provider of the data network to control sampled volumes in relation to the desired accuracy. The control can be either static or can be dynamic for cases in which the data volumes are changing as a function of time.
摘要翻译： 本发明提供了用于对数据网络中的数据流进行采样以便估计网络中的总数据量的装置。 对数据网络中的数据流进行抽样可以减少网络必须花费的网络资源来支持相关的活动。 本发明使得数据网络的服务提供商能够相对于期望的精度来控制采样量。 控制可以是静态的，也可以是数据卷随着时间的变化而变化的情况。
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4.发明授权Method and apparatus for size-dependent sampling for managing a data network 有权用于管理数据网络的大小依赖抽样的方法和装置公开(公告)号：US07080136B2
公开(公告)日：2006-07-18
申请号：US10056683
申请日：2002-01-24
IPC分类号： F06F15/16
CPC分类号： H04L43/00 , H04L12/14 , H04L41/0896 , H04L41/5009 , H04L43/024 , H04L43/026 , H04L43/028 , H04L43/16
摘要： The present invention provides a method and apparatus for sampling data flows in a data network in order to estimate a total data volume in the network. Sampling the data flows In the data network reduces the network resources that must be expended by the network to support the associated activity. The present Invention enables the service provider of the data network to control sampled volumes in relation to the desired accuracy. The control can be either static or can be dynamic for cases in which the data volumes are changing as a function of time.
摘要翻译： 本发明提供了一种用于在数据网络中采样数据流以便估计网络中的总数据量的方法和装置。 对数据流进行采样在数据网络中，减少网络必须花费的网络资源来支持相关活动。 本发明使得数据网络的服务提供商能够相对于期望的精度控制采样的体积。 控制可以是静态的，也可以是数据卷随着时间的变化而变化的情况。
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公开(公告)号：US08028055B2
公开(公告)日：2011-09-27
申请号：US12272712
申请日：2008-11-17
IPC分类号： G06F15/173
CPC分类号： H04L12/14 , H04L12/1428 , H04L41/0896 , H04L41/5009 , H04L43/022 , H04L43/024 , H04L43/026 , H04L43/16 , H04L63/1408 , Y02D50/30
摘要： Two regularized estimators that avoid the pathologies associated with variance estimation are disclosed. The regularized variance estimator adds a contribution to estimated variance representing the likely error, and hence ameliorates the pathologies of estimating small variances while at the same time allowing more reliable estimates to be balanced in the convex combination estimator. The bounded variance estimator employs an upper bound to the variance which avoids estimation pathologies when sampling probabilities are very small.
摘要翻译： 公开了避免与方差估计相关的病理学的两个正则化估计。 正则化方差估计器对代表可能误差的估计方差增加了一个贡献，从而改善了估计小变异的病态，同时允许在凸组合估计中平衡更可靠的估计。 有界方差估计器采用方差的上限，避免了当抽样概率非常小时的估计病变。
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6.发明授权公开(公告)号：US07746808B2
公开(公告)日：2010-06-29
申请号：US12136725
申请日：2008-06-10
申请人： Nicholas Duffield , Edith Cohen , Haim Kaplan , Carsten Lund , Mikkel Thorup
发明人： Nicholas Duffield , Edith Cohen , Haim Kaplan , Carsten Lund , Mikkel Thorup
IPC分类号： H04L12/26
CPC分类号： H04L43/024
摘要： The invention relates to streaming algorithms useful for obtaining summaries over unaggregated packet streams and for providing unbiased estimators for characteristics, such as, the amount of traffic that belongs to a specified subpopulation of flows. Packets are sampled from a packet stream and aggregated into flows and counted by implementation of Adaptive Sample-and-Hold (ASH) or Adaptive NetFlow (ANF), adjusting the sampling rate based on a quantity of flows to obtain a sketch having a predetermined size, the sampling rate being adjusted in steps; and transferring the count of aggregated packets from SRAM to DRAM and initializing the count in SRAM following adjustment of the sampling rate.
摘要翻译： 本发明涉及用于在未分组的分组流上获得摘要的用于提供用于特征的无偏估计器的流式传输算法，例如属于指定的流量子群的业务量。 分组从分组流中采样并聚合成流，并通过实施自适应采样保持（ASH）或自适应净流（ANF）进行计数，根据流量调整采样率，以获得具有预定尺寸的草图 采样率逐步调整; 并将汇总数据包从SRAM传输到DRAM，并在采样率调整后初始化SRAM中的计数。
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公开(公告)号：US20080043636A1
公开(公告)日：2008-02-21
申请号：US11924329
申请日：2007-10-25
申请人： Nicholas Duffield , Carsten Lund , Mikkel Thorup
发明人： Nicholas Duffield , Carsten Lund , Mikkel Thorup
CPC分类号： H04L43/00 , H04L12/14 , H04L41/0896 , H04L41/5009 , H04L43/024 , H04L43/026 , H04L43/028 , H04L43/16
摘要： The present invention provides apparatus for sampling data flows in a data network in order to estimate a total data volume in the network. Sampling the data flows in the data network reduces the network resources that must be expended by the network to support the associated activity. The present invention enables the service provider of the data network to control sampled volumes in relation to the desired accuracy. The control can be either static or can be dynamic for cases in which the data volumes are changing as a function of time.
摘要翻译： 本发明提供了用于对数据网络中的数据流进行采样以便估计网络中的总数据量的装置。 对数据网络中的数据流进行抽样可以减少网络必须花费的网络资源来支持相关的活动。 本发明使得数据网络的服务提供商能够相对于期望的精度来控制采样量。 控制可以是静态的，也可以是数据卷随着时间的变化而变化的情况。
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公开(公告)号：US08005949B2
公开(公告)日：2011-08-23
申请号：US12325340
申请日：2008-12-01
申请人： Nicholas Duffield , Carsten Lund , Mikkel Thorup , Edith Cohen , Haim Kaplan
发明人： Nicholas Duffield , Carsten Lund , Mikkel Thorup , Edith Cohen , Haim Kaplan
IPC分类号： G06F15/173
CPC分类号： G06F17/18 , H04L41/142 , H04L43/024 , H04L43/16
摘要： The present invention relates to a method of obtaining a generic sample of an input stream. The method is designated as VAROPTk. The method comprises receiving an input stream of items arriving one at a time, and maintaining a sample S of items i. The sample S has a capacity for at most k items i. The sample S is filled with k items i. An nth item i is received. It is determined whether the nth item i should be included in sample S. If the nth item i is included in sample S, then a previously included item i is dropped from sample S. The determination is made based on weights of items without distinguishing between previously included items i and the nth item i. The determination is implemented thereby updating weights of items i in sample S. The method is repeated until no more items are received.
摘要翻译： 本发明涉及一种获得输入流的通用样本的方法。 该方法被指定为VAROPTk。 该方法包括一次接收一个物品的输入流，并且保持项目i的样本S. 样本S具有最多k个项目i的容量。 样本S填充有k个项目i。 收到第n项。 确定第n个项目i是否应该包含在样本S中。如果第n个项目i包括在样本S中，则先前包括的项目i从样本S中丢弃。根据项目的权重进行确定，而不区分 以前包括项目i和第n项目i。 由此实现确定，从而更新样本S中的项目i的权重。重复该方法，直到不再收到项目。
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公开(公告)号：US07852785B2
公开(公告)日：2010-12-14
申请号：US12119939
申请日：2008-05-13
申请人： Carsten Lund , Edith Cohen , Nicholas Duffield , Alexandre Gerber , Adam Hersh , Oliver Spatscheck , Mikkel Thorup , Frederick True
发明人： Carsten Lund , Edith Cohen , Nicholas Duffield , Alexandre Gerber , Adam Hersh , Oliver Spatscheck , Mikkel Thorup , Frederick True
IPC分类号： G01R31/08
CPC分类号： H04L43/026 , H04L43/022
摘要： The preferred embodiments of the present invention can include sampling packets transmitted over a network based on the content of the packets. If a packet is sampled, the sampling unit can add one or more fields to the sampled packet that can include a field for a number of bytes contained in the packet, a packet count, a flow count, a sampling type, and the like. The sampled packets can be analyzed to discern desired information from the packets. The additional fields that are added to the sampled packets can be used during the analysis.
摘要翻译： 本发明的优选实施例可以包括基于分组的内容对通过网络传输的分组进行抽样。 如果分组被采样，则采样单元可以将一个或多个字段添加到采样分组，该分组可以包括分组中包含的多个字节的字段，分组计数，流量计数，采样类型等。 可以分析采样的分组以从分组中辨别所需的信息。 在分析过程中可以使用添加到采样数据包的附加字段。
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10.发明授权公开(公告)号：US07764625B2
公开(公告)日：2010-07-27
申请号：US12136705
申请日：2008-06-10
申请人： Nicholas Duffield , Edith Cohen , Haim Kaplan , Carsten Lund , Mikkel Thorup
发明人： Nicholas Duffield , Edith Cohen , Haim Kaplan , Carsten Lund , Mikkel Thorup
IPC分类号： H04L12/26
CPC分类号： H04L47/10 , H04L43/024 , H04L43/026 , H04L43/045 , H04L47/22 , H04L47/41 , Y02D50/30
摘要： The invention relates to streaming algorithms useful for obtaining summaries over unaggregated packet streams and for providing unbiased estimators for characteristics, such as, the amount of traffic that belongs to a specified subpopulation of flows. Packets are sampled from a packet stream and aggregated into flows and counted by implementation of: (a) Adaptive Sampled NetFlow (ANF), and adjusted weight (AANF) of a flow (f) is calculated as follows: AANF(f)=i(f)/p′; i(f) being the number of packets counted for a flow f, and p′ being the sampling rate at end of a measurement period; or (b) Adaptive Sample-and-Hold (ASH), and adjusted weight (AASH) of a flow (f) is calculated as follows: AASH(f)=i(f)+(1−p′)/p′; i(f) being the number of packets counted for a flow f, and p′ being the sampling rate at end of a measurement period.
摘要翻译： 本发明涉及用于在未分组的分组流上获得摘要的用于提供用于特征的无偏估计器的流式传输算法，例如属于指定的流量子群的业务量。 分组从分组流中采样并聚合成流，并通过实现计算：（a）自适应采样NetFlow（ANF）和流（f）的调整权重（AANF）计算如下：AANF（f）= i （f）/ p'; i（f）是流f计数的分组数，p'是测量周期结束时的采样率; 或（b）自适应采样保持（ASH）和流（f）的调整权重（AASH）如下计算：AASH（f）= i（f）+（1-p'）/ p' ; i（f）是流f计数的分组数，p'是测量周期结束时的采样率。
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