PT118348A - Um sistema auto-adaptativo de correlação de falhas baseado em matrizes de causalidade e aprendizagem de máquina - Google Patents

Um sistema auto-adaptativo de correlação de falhas baseado em matrizes de causalidade e aprendizagem de máquina

Info

Publication number
PT118348A
PT118348A PT118348A PT11834822A PT118348A PT 118348 A PT118348 A PT 118348A PT 118348 A PT118348 A PT 118348A PT 11834822 A PT11834822 A PT 11834822A PT 118348 A PT118348 A PT 118348A
Authority
PT
Portugal
Prior art keywords
causality
self
correlation system
fault correlation
matrics
Prior art date
Application number
PT118348A
Other languages
English (en)
Inventor
Guilherme Varela Araújo Carlos
Jorge Rito Lima Pedro
Original Assignee
Altice Labs S A
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Altice Labs S A filed Critical Altice Labs S A
Priority to PT118348A priority Critical patent/PT118348A/pt
Priority to PCT/EP2023/025486 priority patent/WO2024104614A1/en
Priority to EP23848469.5A priority patent/EP4620171A1/en
Publication of PT118348A publication Critical patent/PT118348A/pt

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/147—Network analysis or design for predicting network behaviour
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
    • H04L41/064—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis involving time analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/142—Network analysis or design using statistical or mathematical methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/06—Generation of reports
    • H04L43/067—Generation of reports using time frame reporting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Software Systems (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Algebra (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Probability & Statistics with Applications (AREA)
  • Pure & Applied Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

A PRESENTE INVENÇÃO DESCREVE UM SISTEMA AUTO-ADAPTATIVO CAPAZ DE EXTRAIR CORRELAÇÕES ENTRE MÚLTIPLAS FALHAS A PARTIR DE TOPOLOGIAS DE REDE, COM A COMPONENTE INOVADORA COMO SENDO A FASE DE PRÉ-PROCESSAMENTO DE DADOS GERANDO MATRIZES DE CAUSALIDADE PARA PROPORCIONAR COMO UMA ENTRADA PARA OS MODELOS DE ML. O SISTEMA DE CORRELAÇÃO DE FALHAS PROPOSTO É RESPONSÁVEL POR, SEM QUALQUER CONFIGURAÇÃO, IDENTIFICAR O RELACIONAMENTO HIERÁRQUICO ENTRE OS MÚLTIPLOS ALARMES, PERMITINDO UMA MELHOR COMPREENSÃO DA CAUSALIDADE E DO IMPACTO DE CADA FUNCIONAMENTO DEFEITUOSO, AUXILIANDO ASSIM NA IMPLEMENTAÇÃO DAS REGRAS DE RCA. ISTO PERMITE, NÃO SÓ UMA ENORME REDUÇÃO DE DIMENSIONALIDADE DOS ALARMES NECESSÁRIOS PARA SEREM PROCESSADOS PELOS TO¿S, MAS TAMBÉM AUMENTA SIGNIFICATIVAMENTE O CONHECIMENTO ACERCA DA TOPOLOGIA, REDUZINDO DESSE MODO O TEMPO DE INATIVIDADE E AUMENTANDO A QUALIDADE DE SERVIÇO DA REDE E DOS SERVIÇOS.
PT118348A 2022-11-16 2022-11-16 Um sistema auto-adaptativo de correlação de falhas baseado em matrizes de causalidade e aprendizagem de máquina PT118348A (pt)

Priority Applications (3)

Application Number Priority Date Filing Date Title
PT118348A PT118348A (pt) 2022-11-16 2022-11-16 Um sistema auto-adaptativo de correlação de falhas baseado em matrizes de causalidade e aprendizagem de máquina
PCT/EP2023/025486 WO2024104614A1 (en) 2022-11-16 2023-11-16 A self-adaptive fault correlation system based on causality matrices and machine learning
EP23848469.5A EP4620171A1 (en) 2022-11-16 2023-11-16 A self-adaptive fault correlation system based on causality matrices and machine learning

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PT118348A PT118348A (pt) 2022-11-16 2022-11-16 Um sistema auto-adaptativo de correlação de falhas baseado em matrizes de causalidade e aprendizagem de máquina

Publications (1)

Publication Number Publication Date
PT118348A true PT118348A (pt) 2024-05-16

Family

ID=89845337

Family Applications (1)

Application Number Title Priority Date Filing Date
PT118348A PT118348A (pt) 2022-11-16 2022-11-16 Um sistema auto-adaptativo de correlação de falhas baseado em matrizes de causalidade e aprendizagem de máquina

Country Status (3)

Country Link
EP (1) EP4620171A1 (pt)
PT (1) PT118348A (pt)
WO (1) WO2024104614A1 (pt)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119204155A (zh) * 2024-11-27 2024-12-27 中科南京人工智能创新研究院 基于分布式强化学习的水下探测器集群自适应探测方法与系统

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12250131B2 (en) * 2019-09-11 2025-03-11 Telefonaktiebolaget Lm Ericsson (Publ) Method and apparatus for managing prediction of network anomalies
CN114026828B (zh) * 2020-04-07 2023-03-28 华为技术有限公司 用于监控通信网络的设备和方法
WO2022103738A1 (en) * 2020-11-10 2022-05-19 Globalwafers Co., Ltd. Systems and methods for enhanced machine learning using hierarchical prediction and compound thresholds

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119204155A (zh) * 2024-11-27 2024-12-27 中科南京人工智能创新研究院 基于分布式强化学习的水下探测器集群自适应探测方法与系统

Also Published As

Publication number Publication date
EP4620171A1 (en) 2025-09-24
WO2024104614A1 (en) 2024-05-23

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