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Exploiting functional connectivity inference for efficient root cause analysis

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conference contribution
posted on 2023-06-07, 07:54 authored by Giles WinchesterGiles Winchester, George ParisisGeorge Parisis, Luc BerthouzeLuc Berthouze
A crucial step in remedying faults within network infrastructure is to determine their root cause. However, the large-scale, complex and dynamic nature of modern architecture makes root cause analysis challenging. Statistical approaches for causal inference are promising, however, their deployment has been historically limited due to their high time complexity. In this paper we propose a general framework for leveraging the concept of functional connectivity to reduce the computational overhead of causal inference algorithms. We demonstrate on synthetic data that our approach can achieve substantial speedups when combined with state-of-the-art causal discovery algorithms, with only a small cost in terms of loss of causal information in some cases.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium

ISSN

1542-1201

Publisher

IEEE

Event name

IEEE/IFIP Network Operations and Management Symposium

Event location

Budapest, Hungary

Event type

conference

Event date

25 Apr 2022 - 29 Apr 2022

ISBN

9781665406024

Department affiliated with

  • Informatics Publications

Notes

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2022-03-16

First Open Access (FOA) Date

2022-03-16

First Compliant Deposit (FCD) Date

2022-03-16

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