US 11,936,542 B2
Method of solving problem of network and apparatus for performing the same
Sangkyu Park, Suwon-si (KR); Jonghwa Park, Suwon-si (KR); Youngsuk Sun, Suwon-si (KR); Yunju Lee, Suwon-si (KR); Panhyung Lee, Suwon-si (KR); and Hakyung Jung, Suwon-si (KR)
Assigned to Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed by Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed on May 31, 2022, as Appl. No. 17/828,579.
Application 17/828,579 is a continuation of application No. PCT/KR2022/003410, filed on Mar. 11, 2022.
Claims priority of application No. 10-2021-0043101 (KR), filed on Apr. 2, 2021.
Prior Publication US 2022/0321439 A1, Oct. 6, 2022
Int. Cl. H04L 43/08 (2022.01); H04L 41/14 (2022.01)
CPC H04L 43/08 (2013.01) [H04L 41/145 (2013.01)] 11 Claims
OG exemplary drawing
 
1. An electronic device comprising:
at least one processor,
wherein the at least one processor is configured to:
determine a representative cause representing a cause of each anomaly sample of a quality indicator indicating a quality of a network,
perform a time-series analysis on an indicator associated with the representative cause,
propose a solution corresponding to the representative cause and a result of the time-series analysis,
determine a first time interval for detecting an anomaly of the quality indicator indicating the quality of the network,
detect one or more anomaly samples of the quality indicator of the network during the first time interval,
determine a representative cause representing a cause of each of the one or more anomaly samples,
perform a time-series analysis on an indicator associated with the representative cause during a second time interval comprising the first time interval,
determine the second time interval comprising the first time interval,
determine the indicator associated with the representative cause,
perform the time-series analysis on the indicator associated with the representative cause during the second time interval, and
determine a time corresponding to a predetermined sample prior to a start time of the first time interval as a start time of the second time interval,
wherein the at least one processor is configured to:
determine a cause of each of one or more anomaly samples, and
determine a representative cause representing causes of the one or more anomaly samples, and
wherein the at least one processor is configured to:
input the one or more anomaly samples to a neural network that is trained based on a plurality of pieces of training data associated with a corresponding relationship between an anomaly sample and a cause, and
determine a cause of each of the one or more anomaly samples from an output of the neural network.