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A Taxonomy of Techniques for SLO Failure Prediction in Software Systems

Please always quote using this URN: urn:nbn:de:bvb:20-opus-200594
  • Failure prediction is an important aspect of self-aware computing systems. Therefore, a multitude of different approaches has been proposed in the literature over the past few years. In this work, we propose a taxonomy for organizing works focusing on the prediction of Service Level Objective (SLO) failures. Our taxonomy classifies related work along the dimensions of the prediction target (e.g., anomaly detection, performance prediction, or failure prediction), the time horizon (e.g., detection or prediction, online or offline application),Failure prediction is an important aspect of self-aware computing systems. Therefore, a multitude of different approaches has been proposed in the literature over the past few years. In this work, we propose a taxonomy for organizing works focusing on the prediction of Service Level Objective (SLO) failures. Our taxonomy classifies related work along the dimensions of the prediction target (e.g., anomaly detection, performance prediction, or failure prediction), the time horizon (e.g., detection or prediction, online or offline application), and the applied modeling type (e.g., time series forecasting, machine learning, or queueing theory). The classification is derived based on a systematic mapping of relevant papers in the area. Additionally, we give an overview of different techniques in each sub-group and address remaining challenges in order to guide future research.show moreshow less

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Metadaten
Author: Johannes Grohmann, Nikolas Herbst, Avi Chalbani, Yair Arian, Noam Peretz, Samuel Kounev
URN:urn:nbn:de:bvb:20-opus-200594
Document Type:Journal article
Faculties:Fakultät für Mathematik und Informatik / Institut für Informatik
Language:English
Parent Title (English):Computers
ISSN:2073-431X
Year of Completion:2020
Volume:9
Issue:1
Pagenumber:10
Source:Computers 2020, 9(1), 10; https://doi.org/10.3390/computers9010010
DOI:https://doi.org/10.3390/computers9010010
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Tag:anomaly detection; anomaly prediction; failure prediction; performance prediction; self-adaptive systems; self-aware computing; survey; taxonomy
Release Date:2020/08/31
Date of first Publication:2020/02/11
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International