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公开(公告)号：US20200037392A1
公开(公告)日：2020-01-30
申请号：US16520152
申请日：2019-07-23
Applicant: Samsung Electronics Co., Ltd.
Inventor： Wenxun Qui , Hao Chen , Matthew Tonnemacher , In-sick Jung , Jihoon Sung , Khuong N. Nguyen , Abhishek Sehgal , Jianhua Mo , Jianzhong Zhang , Junyeop Jung , John Wensowitch , Eric Johnson , Namjoon Park
Abstract: A method of an electronic device for a connection management is provided. The method comprises: establishing a communication link with an access point (AP); receiving a triggering indication based on link information measured by the electronic device; determining a quality of the communication link between the electronic device and the AP based on the received triggering indication; comparing, based on the determined quality of the communication link, at least two Q values fetched from a Q table that is determined according to context in which in the electronic device is being used; setting a quantized aggressive index (QAI) value based on the compared at least two Q values; and generating a disconnection command based on the QAI value, wherein the disconnection command is a physical disconnection command or a virtual disconnection command of the communication link between the electronic device and the AP.
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公开(公告)号：US11496353B2
公开(公告)日：2022-11-08
申请号：US15929951
申请日：2020-05-29
Applicant: Samsung Electronics Co., Ltd
Inventor： Vikram Chandrasekhar , Yongseok Park , Shan Jin , Pranav Madadi , Eric Johnson , Jianzhong Zhang , Russell Ford
IPC: H04L41/0631 , H04L41/16 , G06N5/04 , G06N20/00
Abstract: A method for discovering and diagnosing network anomalies. The method includes receiving key performance indicator (KPI) data and alarm data. The method includes extracting features based on samples obtained by discretizing the KPI data and the alarm data. The method includes generating a set of rules based on the features. The method includes identifying a sample as a normal sample or an anomaly sample. In response to identifying the sample as the anomaly sample, the method includes identifying a first rule that corresponds to the sample, wherein the first rule indicates symptoms and root causes of an anomaly included in the sample. The method further includes applying the root causes to derive a root cause explanation of the anomaly and performing a corrective action to resolve the anomaly based on the first rule.
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公开(公告)号：US11284473B2
公开(公告)日：2022-03-22
申请号：US16520152
申请日：2019-07-23
Applicant: Samsung Electronics Co., Ltd.
Inventor： Wenxun Qiu , Hao Chen , Matthew Tonnemacher , In-sick Jung , Jihoon Sung , Khuong N. Nguyen , Abhishek Sehgal , Jianhua Mo , Jianzhong Zhang , Junyeop Jung , John Wensowitch , Eric Johnson , Namjoon Park
Abstract: A method of an electronic device for a connection management is provided. The method comprises: establishing a communication link with an access point (AP); receiving a triggering indication based on link information measured by the electronic device; determining a quality of the communication link between the electronic device and the AP based on the received triggering indication; comparing, based on the determined quality of the communication link, at least two Q values fetched from a Q table that is determined according to context in which in the electronic device is being used; setting a quantized aggressive index (QAI) value based on the compared at least two Q values; and generating a disconnection command based on the QAI value, wherein the disconnection command is a physical disconnection command or a virtual disconnection command of the communication link between the electronic device and the AP.
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公开(公告)号：US20200382361A1
公开(公告)日：2020-12-03
申请号：US15929951
申请日：2020-05-29
Applicant: Samsung Electronics Co., Ltd
Inventor： Vikram Chandrasekhar , Yongseok Park , Shan Jin , Pranav Madadi , Eric Johnson , Jianzhong Zhang , Russell Ford
Abstract: A method for discovering and diagnosing network anomalies. The method includes receiving key performance indicator (KPI) data and alarm data. The method includes extracting features based on samples obtained by discretizing the KPI data and the alarm data. The method includes generating a set of rules based on the features. The method includes identifying a sample as a normal sample or an anomaly sample. In response to identifying the sample as the anomaly sample, the method includes identifying a first rule that corresponds to the sample, wherein the first rule indicates symptoms and root causes of an anomaly included in the sample. The method further includes applying the root causes to derive a root cause explanation of the anomaly and performing a corrective action to resolve the anomaly based on the first rule.
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