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Exploiting functional connectivity inference for efficient root cause analysis
conference contribution
posted on 2023-06-07, 07:54 authored by Giles WinchesterGiles Winchester, George ParisisGeorge Parisis, Luc BerthouzeLuc BerthouzeA 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.
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Publication status
- Published
File Version
- Accepted version
Journal
NOMS 2022-2022 IEEE/IFIP Network Operations and Management SymposiumISSN
1542-1201Publisher
IEEEExternal DOI
Event name
IEEE/IFIP Network Operations and Management SymposiumEvent location
Budapest, HungaryEvent type
conferenceEvent date
25 Apr 2022 - 29 Apr 2022ISBN
9781665406024Department 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 worksFull text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2022-03-16First Open Access (FOA) Date
2022-03-16First Compliant Deposit (FCD) Date
2022-03-16Usage metrics
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