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1. 发明授权

US08797851B2 Locating traffic reduction utilities in communication networks 有权
标题翻译：在通信网络中查找流量减少实用程序
公开(公告)号：US08797851B2
公开(公告)日：2014-08-05
申请号：US13449328
申请日：2012-04-18
申请人： Liane Lewin-Eytan , Joseph Naor
发明人： Liane Lewin-Eytan , Joseph Naor
IPC分类号： G01R31/08
CPC分类号： H04L47/10 , H04L45/125
摘要： A method of locating traffic reduction entities in a communication network, optionally where at least one reduction entity is located within each network path which allows traffic flow between endpoints and central stations. The method comprises assigning a plurality of allocation cost values each estimating cost of locating of one of a plurality of traffic reduction entities on one of a plurality of intermediate nodes of a communication network, calculating a plurality of excess load cost values each calculated according to excess load cost between two adjacent intermediate nodes of the plurality of intermediate nodes, identifying a node set selected from the plurality of intermediate nodes using a target function based on the plurality of cost values and the plurality of excess load cost values, and outputting instructions for locating the plurality of traffic reduction entities on the communication network according to the node set.
摘要翻译：一种在通信网络中定位业务量减少实体的方法，可选地，其中至少一个减少实体位于允许端点和中心站之间的业务流的每个网络路径内。该方法包括：分配多个分配成本值，每个分配成本值估计在通信网络的多个中间节点之一上的多个业务量减少实体中的一个的定位成本，计算多个根据超量计算的超额负载成本值在所述多个中间节点的两个相邻中间节点之间的负载成本，基于所述多个成本值和所述多个成本值以及所述多个过剩负载成本值，使用目标函数来识别从所述多个中间节点中选择的节点集合，以及输出用于定位的指令所述通信网络上的所述多个业务量减少实体根据所述节点集合。

2. 发明申请

US20130279327A1 Locating Traffic Reduction Utilities in Communication Networks 有权
标题翻译：查找通信网络中的流量减少实用程序
公开(公告)号：US20130279327A1
公开(公告)日：2013-10-24
申请号：US13449328
申请日：2012-04-18
申请人： Liane Lewin-Eytan , Joseph Naor
发明人： Liane Lewin-Eytan , Joseph Naor
IPC分类号： H04L12/56
CPC分类号： H04L47/10 , H04L45/125
摘要： A method of locating traffic reduction entities in a communication network, optionally where at least one reduction entity is located within each network path which allows traffic flow between endpoints and central stations. The method comprises assigning a plurality of allocation cost values each estimating cost of locating of one of a plurality of traffic reduction entities on one of a plurality of intermediate nodes of a communication network, calculating a plurality of excess load cost values each calculated according to excess load cost between two adjacent intermediate nodes of the plurality of intermediate nodes, identifying a node set selected from the plurality of intermediate nodes using a target function based on the plurality of cost values and the plurality of excess load cost values, and outputting instructions for locating the plurality of traffic reduction entities on the communication network according to the node set.
摘要翻译：一种在通信网络中定位业务量减少实体的方法，可选地，其中至少一个减少实体位于允许端点和中心站之间的业务流的每个网络路径内。该方法包括：分配多个分配成本值，每个分配成本值估计在通信网络的多个中间节点之一上的多个业务量减少实体中的一个的定位成本，计算多个根据超量计算的超额负载成本值在所述多个中间节点的两个相邻中间节点之间的负载成本，基于所述多个成本值和所述多个成本值以及所述多个过剩负载成本值，使用目标函数来识别从所述多个中间节点中选择的节点集合，以及输出用于定位的指令所述通信网络上的所述多个业务量减少实体根据所述节点集合。

3. 发明授权

US08781768B2 Data reduction in a multi-node system 有权
标题翻译：多节点系统中的数据减少
公开(公告)号：US08781768B2
公开(公告)日：2014-07-15
申请号：US12836605
申请日：2010-07-15
申请人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
发明人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
IPC分类号： G01R21/00
CPC分类号： H04Q9/00 , H04Q2209/30 , H04Q2209/40 , H04Q2209/60 , H04Q2209/84
摘要： An advanced metering infrastructure comprises intermediate nodes. The intermediate nodes receive data from child nodes and aggregate the data according to groups of child nodes. The aggregation provides for a reduced version of the data. The reduction is performed based on groups determined by clustering. The reduced version of the data comprises data describing a group of measurements over time, such as a centroid in an n-dimension space, number of customers in the group, radius of the group and the like. The centroid may shift over time based on a consumption profile, such as low consumption at noon, and high consumption at evening. The consumption profiles may be determined in a learning phase, as well as shifting of centroids of each group over time.
摘要翻译：先进的计量基础设施包括中间节点。中间节点从子节点接收数据，并根据子节点组聚合数据。聚合提供数据的缩减版本。基于通过聚类确定的组来执行缩减。数据的缩减版本包括描述一段时间内的一组测量的数据，例如n维空间中的质心，组中的客户数量，组的半径等。中心可能会根据消费情况随时间而变化，例如中午消费低，晚上消费高。消费概况可以在学习阶段确定，并且可以随着时间推移各组的质心。

4. 发明授权

US08503298B2 Applying quality aware volume reduction to communication networks 失效
标题翻译：将质量意识的卷减少应用于通信网络
公开(公告)号：US08503298B2
公开(公告)日：2013-08-06
申请号：US13114075
申请日：2011-05-24
申请人： Miriam Allalouf , Gidon Gershinsky , Liane Lewin-Eytan , Joseph Erwin Naor
发明人： Miriam Allalouf , Gidon Gershinsky , Liane Lewin-Eytan , Joseph Erwin Naor
IPC分类号： H04J1/16
CPC分类号： H04L41/145 , H04L41/0823 , H04L41/0826 , H04L41/083 , H04L41/0896 , H04L47/762 , Y04S40/162
摘要： A method of applying a quality-aware volume reduction to communication networks is provided herein. The method includes the following stages: deriving, from the network: a bandwidth capacity limit of the links of the network, and an initial flow rate for each flow transmitted via nodes through the network; obtaining from each one of the nodes, a gain value which corresponds to a quantitative data demand requested by the node and given in terms of data quality; and calculating, for each one of the nodes, a data reduction ratio, that achieves: (i) a maximal overall revenue associated with the network, wherein the revenue for a node is calculated with respect to the quality of the data that arrives to the node, and (ii) an optimal bandwidth allocation over the links with respect to the gains and the data quality at each node, and to the limited bandwidth capacity of the links.
摘要翻译：本文提供了将质量感知体积减小应用于通信网络的方法。该方法包括：从网络导出网络链路的带宽容量限制，以及通过网络通过节点传输的每个流的初始流速; 从每个节点获得对应于节点请求的定量数据需求并且根据数据质量给出的增益值; 以及为每个所述节点计算数据缩减比率，其实现：（i）与所述网络相关联的最大总收入，其中针对到达所述节点的数据的质量来计算节点的收入节点，以及（ii）关于每个节点处的增益和数据质量的链路上的最佳带宽分配以及链路的有限带宽容量。

5. 发明申请

US20110184676A1 DATA REDUCTION IN A MULTI-NODE SYSTEM 有权
标题翻译：多节点系统中的数据减少
公开(公告)号：US20110184676A1
公开(公告)日：2011-07-28
申请号：US12836605
申请日：2010-07-15
申请人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
发明人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
IPC分类号： G06F19/00 , G01R21/00
CPC分类号： H04Q9/00 , H04Q2209/30 , H04Q2209/40 , H04Q2209/60 , H04Q2209/84
摘要： An advanced metering infrastructure comprises intermediate nodes. The intermediate nodes receive data from child nodes and aggregate the data according to groups of child nodes. The aggregation provides for a reduced version of the data. The reduction is performed based on groups determined by clustering. The reduced version of the data comprises data describing a group of measurements over time, such as a centroid in an n-dimension space, number of customers in the group, radius of the group and the like. The centroid may shift over time based on a consumption profile, such as low consumption at noon, and high consumption at evening. The consumption profiles may be determined in a learning phase, as well as shifting of centroids of each group over time.
摘要翻译：先进的计量基础设施包括中间节点。中间节点从子节点接收数据，并根据子节点组聚合数据。聚合提供数据的缩减版本。基于通过聚类确定的组来执行缩减。数据的缩减版本包括描述一段时间内的一组测量的数据，例如n维空间中的质心，组中的客户数量，组的半径等。中心可能会根据消费情况随时间而变化，例如中午消费低，晚上消费高。消费概况可以在学习阶段确定，并且可以随着时间推移各组的质心。

6. 发明申请

US20110181437A1 DATA REDUCTION IN A MULTI-NODE SYSTEM 有权
标题翻译：多节点系统中的数据减少
公开(公告)号：US20110181437A1
公开(公告)日：2011-07-28
申请号：US12836627
申请日：2010-07-15
申请人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
发明人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
IPC分类号： G08C15/06 , G08C19/16 , G08B21/00
CPC分类号： H04Q9/00 , H04Q2209/30 , H04Q2209/40 , H04Q2209/60 , H04Q2209/84
摘要： An advanced metering infrastructure comprises intermediate nodes. The intermediate nodes receive data from child nodes and relay a subset of the data that is not according to an expected value. The expected value may be determined based on a forecasting function computed based on past data. The expected value may be a spatial shape in an n-dimension space. A data not within the spatial shape may be considered not in accordance with the expected value. In some case, the spatial shape is defined by a centroid and a radius. The spatial shape may shift over time based on a consumption profile, such as low consumption at noon, and high consumption at evening. The consumption profiles may be determined in a learning phase, as well as shifting of spatial shapes of each group over time.
摘要翻译：先进的计量基础设施包括中间节点。中间节点从子节点接收数据，并中继不符合预期值的数据子集。期望值可以基于基于过去数据计算的预测函数来确定。期望值可以是n维空间中的空间形状。不在空间形状内的数据可以被认为不符合预期值。在某些情况下，空间形状由质心和半径定义。空间形状可能会根据消费情况随时间而变化，例如中午消费低，晚上消费高。消费概况可以在学习阶段中确定，并且可以随着时间推移各组的空间形状。

7. 发明授权

US08797864B2 Adaptive traffic management via analytics based volume reduction 有权
标题翻译：通过基于分析的量减少的自适应流量管理
公开(公告)号：US08797864B2
公开(公告)日：2014-08-05
申请号：US13008918
申请日：2011-01-19
申请人： Gidon Gershinsky , Liane Lewin-Eytan , Konstantin Shagin
发明人： Gidon Gershinsky , Liane Lewin-Eytan , Konstantin Shagin
IPC分类号： H04L12/56
CPC分类号： H04L47/22 , H04L47/12 , H04L47/32
摘要： A method of managing traffic over a communication link between a transmitting node and a receiving node is provided herein. The method includes: determining momentary traffic shaping constraints; accumulating incoming messages at the transmitting node into a data queue, based on the momentary traffic shaping constraints; transmitting the messages from the data queue to the receiving node over the communication link based on the momentary traffic shaping constraints; estimating a desired amount of data that needs to be discarded from messages in the data queue, based on: (a) the size of the data queue and (b) the momentary traffic shaping constraints; sorting data in the data queue by an order of importance, based on analytic objects; discarding, based on the analytic objects, the desired amount of data from the messages in the queued data, such that the discarded data is ranked lowest by the order of importance.
摘要翻译：本文提供了一种在发送节点和接收节点之间的通信链路上管理业务的方法。该方法包括：确定瞬时流量整形约束; 基于瞬时流量整形约束将发送节点处的进入消息累加到数据队列中; 基于瞬时流量整形约束，通过通信链路将消息从数据队列发送到接收节点; 基于：（a）数据队列的大小和（b）瞬时流量整形约束，从数据队列中的消息估计需要丢弃的数据量; 基于分析对象，按照重要性顺序对数据队列中的数据进行排序; 基于分析对象，从排队数据中的消息中丢弃期望的数据量，使得丢弃的数据按重要程度排列最低。

8. 发明申请

US20130176855A1 DYNAMIC MAPPING IN A MULTICASTING ENVIRONMENT 失效
标题翻译：多元环境中的动态绘图
公开(公告)号：US20130176855A1
公开(公告)日：2013-07-11
申请号：US13346747
申请日：2012-01-10
申请人： Liane Lewin-Eytan , Nir Naaman , Shahar Chen , Yoav Tock
发明人： Liane Lewin-Eytan , Nir Naaman , Shahar Chen , Yoav Tock
IPC分类号： H04W24/02 , H04W4/06
CPC分类号： H04L29/06455 , H04L29/06482 , H04L65/4076 , H04L65/601
摘要： Enhancing performance in a multicasting system comprising monitoring filtering costs in a multicasting system as system characteristics change over time, wherein the multicasting system is operating based on a first mapping, between a plurality of data flows and multicasting groups, to disseminate data to users that subscribe to one or more of the data flows; computing a second mapping in response to determining that overhead associated with filtering of unwanted flows at the user level has exceeded a threshold; and transitioning the multicasting system from using the first mapping to using the second mapping, in response to determining that the second mapping is feasible as applicable to one or more constraints associated with the multicasting system.
摘要翻译：提高组播系统中的性能，包括当系统特性随时间变化时监视组播系统中的过滤成本，其中组播系统基于多个数据流和组播组之间的第一映射进行操作，以向订阅的用户传播数据到一个或多个数据流; 响应于确定与在用户级别的不需要的流的过滤相关联的开销已经超过阈值来计算第二映射; 以及响应于确定所述第二映射适用于与所述多播系统相关联的一个或多个约束是可行的，并且将所述多播系统从使用所述第一映射转变为使用所述第二映射。

9. 发明申请

US20120300627A1 APPLYING QUALITY AWARE VOLUME REDUCTION TO COMMUNICATION NETWORKS 失效
标题翻译：将质量注意量减少到通信网络
公开(公告)号：US20120300627A1
公开(公告)日：2012-11-29
申请号：US13114075
申请日：2011-05-24
申请人： Miriam Allalouf , Gidon Gershinsky , Liane Lewin-Eytan
发明人： Miriam Allalouf , Gidon Gershinsky , Liane Lewin-Eytan
IPC分类号： H04L12/26
CPC分类号： H04L41/145 , H04L41/0823 , H04L41/0826 , H04L41/083 , H04L41/0896 , H04L47/762 , Y04S40/162
摘要： A method of applying a quality-aware volume reduction to communication networks is provided herein. The method includes the following stages: deriving, from the network: a bandwidth capacity limit of the links of the network, and an initial flow rate for each flow transmitted via nodes through the network; obtaining from each one of the nodes, a gain value which corresponds to a quantitative data demand requested by the node and given in terms of data quality; and calculating, for each one of the nodes, a data reduction ratio, that achieves: (i) a maximal overall revenue associated with the network, wherein the revenue for a node is calculated with respect to the quality of the data that arrives to the node, and (ii) an optimal bandwidth allocation over the links with respect to the gains and the data quality at each node, and to the limited bandwidth capacity of the links.
摘要翻译：本文提供了将质量感知体积减小应用于通信网络的方法。该方法包括：从网络导出网络链路的带宽容量限制，以及通过网络通过节点传输的每个流的初始流速; 从每个节点获得对应于节点请求的定量数据需求并且根据数据质量给出的增益值; 以及为每个所述节点计算数据缩减比率，其实现：（i）与所述网络相关联的最大总收入，其中针对到达所述节点的数据的质量来计算节点的收入节点，以及（ii）关于每个节点处的增益和数据质量的链路上的最佳带宽分配以及链路的有限带宽容量。

10. 发明授权

US08810429B2 Data forecasting in a multi-node system 有权
标题翻译：多节点系统中的数据预测
公开(公告)号：US08810429B2
公开(公告)日：2014-08-19
申请号：US12836627
申请日：2010-07-15
申请人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
发明人： Gidon Gershinsky , Liane Lewin-Eytan , Yossi Richter , Konstantin Shagin , Elad Yom-Tov
IPC分类号： G01D4/00 , G01R22/06 , G01R21/00
CPC分类号： H04Q9/00 , H04Q2209/30 , H04Q2209/40 , H04Q2209/60 , H04Q2209/84
摘要： An advanced metering infrastructure comprises intermediate nodes. The intermediate nodes receive data from child nodes and relay a subset of the data that is not according to an expected value. The expected value may be determined based on a forecasting function computed based on past data. The expected value may be a spatial shape in an n-dimension space. A data not within the spatial shape may be considered not in accordance with the expected value. In some case, the spatial shape is defined by a centroid and a radius. The spatial shape may shift over time based on a consumption profile, such as low consumption at noon, and high consumption at evening. The consumption profiles may be determined in a learning phase, as well as shifting of spatial shapes of each group over time.
摘要翻译：先进的计量基础设施包括中间节点。中间节点从子节点接收数据，并中继不符合预期值的数据子集。期望值可以基于基于过去数据计算的预测函数来确定。期望值可以是n维空间中的空间形状。不在空间形状内的数据可以被认为不符合预期值。在某些情况下，空间形状由质心和半径定义。空间形状可能会根据消费情况随时间而变化，例如中午消费低，晚上消费高。消费概况可以在学习阶段中确定，并且可以随着时间推移各组的空间形状。

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