Evaluation of synthetically generated traces towards a data-centre digital twin
Authors:
- Alejandro Fernández-Montes,
- Dámian Fernández-Cerero,
- Agnieszka Jakóbik,
- Belèn Bermejo,
- Carlos Juiz
Abstract
Several approaches exist to generate synthetic data centre traces for various purposes: from augmenting operational traces for data centre simulators and digital twins to forecasting incoming workload to improve data centre behaviour. The evaluation of the quality of synthetically generated multivariate time-series datasets, such as those related to data-centre traces, is not a trivial task, since complex patterns and correlation between variables may be present. This paper proposes a new multivariate time-series evaluation framework that computes a set of metrics and figures that can be used to measure the quality of synthetically generated data-centre traces. We then employ the proposed tool to compare two synthetic data centre traces with the original trace and assess their quality. These synthetic traces have been generated by means of Generative Adversarial Networks (GAN). In this work, we employ TimeGAN, a GAN model focused on the generation of multivariate time series traces. We finally show how the proposed framework provides us with a set of metrics consistent with the observable behaviour and numerical insights on the quality of the generated data centre traces, which are hard to acquire otherwise.
- Record ID
- CUT3a6c2e3c56ae44b8b7b1ab51616c6317
- Publication categories
- ; ;
- Author
- Pages
- 528-534
- Other elements of collation
- tab.; wykr.; Bibliografia (na s.) - 533; Bibliografia (liczba pozycji) - 10; Oznaczenie streszczenia - Abstr.
- Substantive notes
- Wydaw. wg cop.
- Miejsce wyd. wg siedziby wydaw.
- Punktacja MNiSW/MEiN (rozdział) - 5
- Book
- Vicario Enrico, Enrico Vicario Bandinelli Romeo, Romeo Bandinelli Fani Virginia Virginia Fani [et al.] (eds.): ECMS 2023 : proceedings of the 37th ECMS International Conference on Modelling and Simulation, June 20th – June 23rd, 2023 Florence, Italy, European Conference for Modelling and Simulation, no. Vol. 37, Iss. 1, 2023, Caserta, ECMS, ISBN 978-3-937436-80-7 (Print)
- Keywords in English
- time-series, synthetic data generation, data centre traces, generative adversarial networks, data augmentation
- URL
- https://www.scs-europe.net/dlib/dl-index.htm Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 5
- Score source
- publisherList
- Score
- Additional fields
- Indeksowana w: CORE
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT3a6c2e3c56ae44b8b7b1ab51616c6317/
- URN
urn:pkr-prod:CUT3a6c2e3c56ae44b8b7b1ab51616c6317
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.