|
|
Digital
Library of the European Council for Modelling and Simulation |
|
Title: |
Metadata For Root Cause Analysis |
|
Authors: |
Alexander A. Grusho, Nick A. Grusho, Michael I. Zabezhailo,
Elena E. Timonina, Vladimir V. Senchilo |
|
Published in:
|
(2021). ECMS 2021,
35th Proceedings DOI: http://doi.org/10.7148/2021 ISSN:
2522-2422 (ONLINE) ISSN:
2522-2414 (PRINT) ISSN:
2522-2430 (CD-ROM) ISBN: 978-3-937436-72-2 Communications of the ECMS , Volume 35, Issue 1, June 2021, United Kingdom |
|
Citation
format: |
Alexander A. Grusho,
Nick A. Grusho, Michael I. Zabezhailo,
Elena E. Timonina, Vladimir V. Senchilo
(2021). Metadata For Root Cause Analysis, ECMS
2021 Proceedings Edited By: Khalid Al-Begain, Mauro
Iacono, Lelio Campanile, Andrzej Bargiela European Council
for Modeling and Simulation. doi:
10.7148/2021-0267 |
|
DOI: |
https://doi.org/10.7148/2021-0267 |
|
Abstract: |
The paper is devoted to the task of finding the root cause of anomaly in a distributed information and computing system. An approximate approach is considered to detect implicit anomalies with accuracy to the object (of a component of the technical device, a node of a network infrastructure, an application or of an information resource). The approximate solution is based on the use of integral parameters that allow you to identify an anomaly, but do not allow you to indicate its cause. To work with such methods for determining the root causes of anomalies, auxiliary data is required, which is called metadata in the work. The work describes a metadata construction algorithm and shows ways of using metadata to build an object in which the root cause of the anomaly is located. An approximate solution to the problem of finding the root cause of an anomaly with a help of quickly computable values of integral parameters is necessary to reduce the time of interruption of work processes due to implicit anomalies. It is assumed that small subsystems and nodes are easier to replace than to delve into the study of the cause. |
|
Full
text: |
|
