Towards Extension of Data Centre Modelling Toolbox with Parameters Estimation

Yulia Berezovskaya*, Chen Wei Yang, Valeriy Vyatkin

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

1 Sitaatiot (Scopus)
44 Lataukset (Pure)

Abstrakti

Modern data centres consume a significant amount of electricity. Therefore, they require techniques for improving energy efficiency and reducing energy waste. The promising energy-saving methods are those, which adapt the system energy use based on resource requirements at run-time. These techniques require testing their performance, reliability and effect on power consumption in data centres. Generally, real data centres cannot be used as a test site because of such experiments may violate safety and security protocols. Therefore, examining the performance of different energy-saving strategies requires a model, which can replace the real data centre. The model is expected to accurately estimate the energy consumption of data centre components depending on their utilisation. This work presents a toolbox for data centre modelling. The toolbox is a set of building blocks representing individual components of a typical data centre. The paper concentrates on parameter estimation methods, which use data, collected from a real data centre and adjust parameters of building blocks so that the model represents the data centre most accurately. The paper also demonstrates the results of parameters estimation on an example of EDGE module of SICS ICE data centre located in Luleå, Sweden.

AlkuperäiskieliEnglanti
OtsikkoTechnological Innovation for Applied AI Systems
AlaotsikkoProceedings of 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021
ToimittajatLuis M. Camarinha-Matos, Pedro Ferreira, Guilherme Brito
KustantajaSpringer
Sivut189-196
Sivumäärä8
ISBN (elektroninen)9783030782887
ISBN (painettu)9783030782870
DOI - pysyväislinkit
TilaJulkaistu - heinäk. 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaAdvanced Doctoral Conference on Computing, Electrical and Industrial Systems - Virtual, Online, Caparica, Portugali
Kesto: 7 heinäk. 20219 heinäk. 2021
Konferenssinumero: 12
https://doceis.dee.fct.unl.pt/

Julkaisusarja

NimiIFIP Advances in Information and Communication Technology
Vuosikerta626
ISSN (painettu)1868-4238
ISSN (elektroninen)1868-422X

Conference

ConferenceAdvanced Doctoral Conference on Computing, Electrical and Industrial Systems
LyhennettäDoCEIS
Maa/AluePortugali
KaupunkiCaparica
Ajanjakso07/07/202109/07/2021
www-osoite

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