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公开(公告)号：US08976661B2
公开(公告)日：2015-03-10
申请号：US13736146
申请日：2013-01-08
Applicant: NEC Laboratories America, Inc.
Inventor： Cristian Lumezanu , Guofei Jiang , Yueping Zhang , Vishal Singh , Ye Wang
IPC: H04L12/26 , H04L12/801 , H04L12/891
CPC classification number: H04L47/12 , H04L43/026 , H04L43/16 , H04L47/2441 , H04L47/41 , H04L63/1425 , Y02D50/30
Abstract: A device used in a network is disclosed. The device includes a network monitor to monitor a network state and to collect statistics for flows going through the network, a flow aggregation unit to aggregate flows into clusters and identify flows that can cause a network problem, and an adaptive control unit to adaptively regulate the identified flow according to network feedback. Other methods and systems also are disclosed.
Abstract translation: 公开了一种在网络中使用的设备。 该设备包括网络监视器，用于监控网络状态并收集通过网络的流量的统计信息;流量聚合单元，用于将流聚集成群集，识别可能导致网络问题的流;以及自适应控制单元， 根据网络反馈确定流量。 还公开了其它方法和系统。
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公开(公告)号：US20150052243A1
公开(公告)日：2015-02-19
申请号：US14456094
申请日：2014-08-11
Applicant: NEC Laboratories America, Inc.
Inventor： Cristian Lumezanu , Kyriakos Zanfis , Guofei Jiang
IPC: H04L12/26
CPC classification number: H04L43/04 , H04L41/046 , H04L41/147 , H04L43/026
Abstract: Systems and methods for network management, including adaptively installing one or more monitoring rules in one or more network devices on a network using an intelligent network middleware, detecting application traffic on the network transparently using an application demand monitor, and predicting future network demands of the network by analyzing historical and current demands. The one or more monitoring rules are updated once counters are collected; and network paths are determined and optimized to meet network demands and maximize utilization and application performance with minimal congestion on the network.
Abstract translation: 网络管理系统和方法，包括使用智能网络中间件在网络上的一个或多个网络设备中自适应地安装一个或多个监控规则，使用应用需求监控器透明地检测网络上的应用流量，以及预测未来网络需求 分析历史和当前需求的网络。 收集计数器后，更新一个或多个监控规则; 并确定和优化网络路径以满足网络需求并最大程度地利用和应用性能，同时网络拥塞最小。
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公开(公告)号：US08924787B2
公开(公告)日：2014-12-30
申请号：US13736158
申请日：2013-01-08
Applicant: NEC Laboratories America, Inc.
Inventor： Cristian Lumezanu , Guofei Jiang , Yueping Zhang , Vishal Singh , Ahsan Arefin
CPC classification number: G06F11/3476 , G06F11/0793 , G06F11/3006 , G06F11/3017 , G06F11/302 , G06F11/3055 , H04L41/142 , H04L41/145 , H04L43/04
Abstract: A debugging system used for a data center in a network is disclosed. The system includes a monitoring engine to monitor network traffic by collecting traffic information from a network controller, a modeling engine to model an application signature, an infrastructure signature, and a task signature using a monitored log, a debugging engine to detect a change in the application signature between a working status and a non-working status using a reference log and a problem log, and to validate the change using the task signature, and a providing unit to provide toubleshooting information, wherein an unknown change in the application signature is correlated to a known problem class by considering a dependency to a change in the infrastructure signature. Other methods and systems also are disclosed.
Abstract translation: 公开了一种用于网络中的数据中心的调试系统。 该系统包括监视引擎，通过从网络控制器收集交通信息，建模引擎来模拟应用签名，基础设施签名和使用监控日志的任务签名来监视网络流量;调试引擎，用于检测网络流量的变化 使用参考日志和问题日志在工作状态和非工作状态之间的应用签名，以及使用所述任务签名来验证所述改变;以及提供单元，用于提供故障排除信息，其中所述应用签名中的未知变化被相关 通过考虑对基础设施签名的改变的依赖性来解决已知的问题类。 还公开了其它方法和系统。
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公开(公告)号：US20130176852A1
公开(公告)日：2013-07-11
申请号：US13736146
申请日：2013-01-08
Applicant: NEC LABORATORIES AMERICA, INC.
Inventor： Cristian Lumezanu , Guofei Jiang , Yueping Zhang , Vishal Singh , Ye Wang
IPC: H04L12/56
CPC classification number: H04L47/12 , H04L43/026 , H04L43/16 , H04L47/2441 , H04L47/41 , H04L63/1425 , Y02D50/30
Abstract: A device used in a network is disclosed. The device includes a network monitor to monitor a network state and to collect statistics for flows going through the network, a flow aggregation unit to aggregate flows into clusters and identify flows that can cause a network problem, and an adaptive control unit to adaptively regulate the identified flow according to network feedback. Other methods and systems also are disclosed.
Abstract translation: 公开了一种在网络中使用的设备。 该设备包括网络监视器，用于监控网络状态并收集通过网络的流量的统计信息;流量聚合单元，用于将流聚集成群集，识别可能导致网络问题的流;以及自适应控制单元， 根据网络反馈确定流量。 还公开了其它方法和系统。
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公开(公告)号：US11543808B2
公开(公告)日：2023-01-03
申请号：US17223251
申请日：2021-04-06
Applicant: NEC Laboratories America, Inc.
Inventor： Dongjin Song , Takehiko Mizoguchi , Cristian Lumezanu , Haifeng Chen
IPC: G05B19/418
Abstract: Methods and systems for detecting and correcting anomalies includes generating historical binary codes from historical time series segments. The historical time series segments are each made up of measurements from respective sensors. A latest binary code is generated from a latest time series segment. It is determined that the latest time series segment represents anomalous behavior, based on a comparison of the latest binary code to the historical binary codes. The sensors are ranked, based on a comparison of time series data of the sensors in the latest time series segment to respective time series data of the historical time series, to generate a sensor ranking. A corrective action is performed responsive to the detected anomaly, prioritized according to the sensor ranking.
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Patent Agency Ranking
公开(公告)号：US20220318627A1
公开(公告)日：2022-10-06
申请号：US17713412
申请日：2022-04-05
Applicant: NEC Laboratories America, Inc.
Inventor： Takehiko Mizoguchi , Cristian Lumezanu , Yuncong Chen , Haifeng Chen
Abstract: Methods and systems for training a model include training a feature extraction model to extract a feature vector from a multivariate time series segment, based on a set of training data corresponding to measurements of a system in a first domain. Adapting the feature extraction model to a second domain, based on prototypes of the training data in the first domain and new time series data corresponding to measurements of the system in a second domain.
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公开(公告)号：US20220075822A1
公开(公告)日：2022-03-10
申请号：US17408852
申请日：2021-08-23
Applicant: NEC Laboratories America, Inc.
Inventor： Cristian Lumezanu , Yuncong Chen , Takehiko Mizoguchi , Dongjin Song , Haifeng Chen , Jurijs Nazarovs
IPC: G06F16/906
Abstract: A method classifies missing labels. The method computes, using a neural network model trained on training data, rank-based statistics of a feature of a time series segment to attempt to select two candidate labels from the training data that the segment most likely belongs to. The method classifies the segment using k-NN-based classification applied to the training data, responsive to the two candidate labels being present in the training data. The method classifies the segment by hypothesis testing, responsive to only one candidate label being present in the training data. The method classifies the segment into a class with higher values of the rank-based statistics from among a plurality of classes with different values of the rank-based statistics, responsive to no candidate labels being present in the training data. The method corrects a prediction by an applicable one of the classifying steps by majority voting with time windows.
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公开(公告)号：US20210341910A1
公开(公告)日：2021-11-04
申请号：US17223251
申请日：2021-04-06
Applicant: NEC Laboratories America, Inc.
Inventor： Dongjin Song , Takehiko Mizoguchi , Cristian Lumezanu , Haifeng Chen
IPC: G05B19/418
Abstract: Methods and systems for detecting and correcting anomalies includes generating historical binary codes from historical time series segments. The historical time series segments are each made up of measurements from respective sensors. A latest binary code is generated from a latest time series segment. It is determined that the latest time series segment represents anomalous behavior, based on a comparison of the latest binary code to the historical binary codes. The sensors are ranked, based on a comparison of time series data of the sensors in the latest time series segment to respective time series data of the historical time series, to generate a sensor ranking. A corrective action is performed responsive to the detected anomaly, prioritized according to the sensor ranking.
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公开(公告)号：US20210065734A1
公开(公告)日：2021-03-04
申请号：US16997249
申请日：2020-08-19
Applicant: NEC Laboratories America, Inc.
Inventor： Cristian Lumezanu , Yuncong Chen , Dongjin Song , Takehiko Mizuguchi , Haifeng Chen , Bo Dong
Abstract: A method is provided. Intermediate audio features are generated from respective segments of an input acoustic time series for a same scene. Using a nearest neighbor search, respective segments of the input acoustic time series are classified based on the intermediate audio features to generate a final intermediate feature as a classification for the input acoustic time series. Each respective segment corresponds to a respective different acoustic window. The generating step includes learning the intermediate audio features from Multi-Frequency Cepstral Component (MFCC) features extracted from the input acoustic time series, dividing the same scene into the different windows having varying MFCC features, and feeding the MFCC features of each window into respective LSTM units such that a hidden state of each respective LSTM unit is passed through an attention layer to identify feature correlations between hidden states at different time steps corresponding to different ones of the different windows.
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40.发明申请公开(公告)号：US20210056127A1
公开(公告)日：2021-02-25
申请号：US16996110
申请日：2020-08-18
Applicant: NEC Laboratories America, Inc.
Inventor： Yuncong Chen , Hao Yuan , Cristian Lumezanu , Haifeng Chen , Takehiko Mizoguchi , Dongjin Song
IPC: G06F16/335 , G06F16/33 , G06F16/35 , G06N20/00
Abstract: A method for embedding learning and clustering for paired multi-modal data using deep canonical correlation analysis and active learning with pairwise queries is presented. The method includes collecting time-series data from a plurality of sensors, training, in an unsupervised manner, a cross-modal retrieval system by using the time-series data and relevant comment texts, depending on a modality of a query, retrieving the relevant comment texts from a time-series segment of the time-series data, the relevant comment texts used as human-readable explanations of a query segment, retrieving relevant time-series segments given a sentence or a set of keywords such that the relevant time-series segments match the sentence or set of keywords, and retrieving the relevant time-series segments given the time-series segment and the sentence or set of keywords such that a first subset of attributes match the set of keywords and a second subset of attributes resembles the time-series segment.
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