NARX-based multi-step ahead response time prediction for database servers

Payam Amani; Maria Kihl; Anders Robertsson

doi:10.1109/ISDA.2011.6121757

NARX-based multi-step ahead response time prediction for database servers

Payam Amani, Maria Kihl, Anders Robertsson

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

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Abstract

Advanced telecommunication applications are often based on a multi-tier architecture, with application servers and database servers. With a rapidly increasing development of cloud computing and data centers, characterizations of the dynamics for database servers during changing workloads will be a key factor for analysis and performance improvements in these applications. We propose a multi-step ahead response time predictor for database queries based on a nonlinear autoregressive neural network model with exogenous inputs. The estimator shows many promising characteristics which make it a viable candidate for being implemented in admission control products for database servers. Performance of the proposed predictor is evaluated through experiments on a lab setup with a MySQL-server.

Original language	English
Title of host publication	[Host publication title missing]
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
Pages	813-818
ISBN (Print)	978-1-4577-1676-8
DOIs	https://doi.org/10.1109/ISDA.2011.6121757
Publication status	Published - 2011
Event	11th International Conference on Intelligent Systems Design and Applications - Cordoba, Spain Duration: 2011 Nov 22 → 2011 Nov 24

Publication series

Name
ISSN (Print)	2164-7143

Conference

Conference	11th International Conference on Intelligent Systems Design and Applications
Country/Territory	Spain
City	Cordoba
Period	2011/11/22 → 2011/11/24

Bibliographical note

key=amani_etal2011isda

Subject classification (UKÄ)

Control Engineering
Electrical Engineering, Electronic Engineering, Information Engineering

Access to Document

10.1109/ISDA.2011.6121757

PID2077899

LCCC
Holmqvist, A. (Researcher), Andersson, N. (Researcher), Cervin, A. (Researcher), Mannesson, A. (Researcher), Gattami, A. (Researcher), Ghulchak, A. (Researcher), Papadopoulos, A. V. (Researcher), Rantzer, A. (Researcher), Robertsson, A. (Researcher), Sootla, A. (Researcher), THEORIN, A. (Researcher), Bernhardsson, B. (Researcher), Olofsson, B. (Researcher), Wittenmark, B. (Researcher), Grussler, C. (Researcher), Johnsson, C. (Researcher), MADJIDIAN, D. (Researcher), Johannesson, E. (Researcher), Magnusson, F. (Researcher), Ståhl, F. (Researcher), Como, G. (Researcher), Chasparis, G. (Researcher), Turesson, G. (Researcher), Dressler, I. (Researcher), Åkesson, J. (Researcher), Cho, J. H. (Researcher), Årzén, K.-E. (Researcher), Åström, K. J. (Researcher), Sou, K. C. (Researcher), Mårtensson, K. (Researcher), Berntorp, K. (Researcher), Soltesz, K. (Researcher), Lessard, L. (Researcher), Hast, M. (Researcher), Rönn, M. (Researcher), Ansbjerg Kjær, M. (Researcher), Maggio, M. (Researcher), Kristalny, M. (Researcher), Garpinger, O. (Researcher), From, P. J. (Researcher), Larsson, P.-O. (Researcher), Giselsson, P. (Researcher), Johansson, R. (Researcher), Hägglund, T. (Researcher), Vladimerou, V. (Researcher), Romero Segovia, V. (Researcher), Aurelius, A. (Researcher), Cedersjö, G. (Researcher), Bür, K. (Researcher), Dellkrantz, M. (Researcher), Du, M. (Researcher), Amani, P. (Researcher), Larsson, R. (Researcher), Tärneberg, W. (Research student), Li, Z. (Researcher), Yin, L. (Researcher), Tufvesson, F. (Researcher), Höst, S. (Researcher), Nilsson, B. (Researcher), Stenström, S. (Researcher), Andersson, J. A. (Researcher), Diehl, S. (Researcher), Dürango, J. (Researcher), Ghazaei Ardakani, M. (Researcher), Forsberg, P.-O. (Researcher), Bengtsson, F. (Researcher), Jörntell, H. (Researcher), Arévalo, C. (Researcher), Führer, C. (Researcher), Andersson, C. (Researcher), Mohammadi, F. (Researcher), Ödling, P. (Researcher), Andersson, M. (Researcher), Kihl, M. (Researcher) & Tunestål, P. (Researcher)
2008/07/01 → 2018/06/30
Project: Research

Cite this

@inproceedings{ffc14c2fee61436f803bf560465decf1,

title = "NARX-based multi-step ahead response time prediction for database servers",

abstract = "Advanced telecommunication applications are often based on a multi-tier architecture, with application servers and database servers. With a rapidly increasing development of cloud computing and data centers, characterizations of the dynamics for database servers during changing workloads will be a key factor for analysis and performance improvements in these applications. We propose a multi-step ahead response time predictor for database queries based on a nonlinear autoregressive neural network model with exogenous inputs. The estimator shows many promising characteristics which make it a viable candidate for being implemented in admission control products for database servers. Performance of the proposed predictor is evaluated through experiments on a lab setup with a MySQL-server.",

author = "Payam Amani and Maria Kihl and Anders Robertsson",

note = "key=amani_etal2011isda; 11th International Conference on Intelligent Systems Design and Applications ; Conference date: 22-11-2011 Through 24-11-2011",

year = "2011",

doi = "10.1109/ISDA.2011.6121757",

language = "English",

isbn = "978-1-4577-1676-8",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

pages = "813--818",

booktitle = "[Host publication title missing]",

address = "United States",

}

Amani, P , Kihl, M & Robertsson, A 2011, NARX-based multi-step ahead response time prediction for database servers. in [Host publication title missing]. IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 813-818, 11th International Conference on Intelligent Systems Design and Applications, Cordoba, Spain, 2011/11/22. https://doi.org/10.1109/ISDA.2011.6121757

TY - GEN

T1 - NARX-based multi-step ahead response time prediction for database servers

AU - Amani, Payam

AU - Kihl, Maria

AU - Robertsson, Anders

N1 - key=amani_etal2011isda

PY - 2011

Y1 - 2011

N2 - Advanced telecommunication applications are often based on a multi-tier architecture, with application servers and database servers. With a rapidly increasing development of cloud computing and data centers, characterizations of the dynamics for database servers during changing workloads will be a key factor for analysis and performance improvements in these applications. We propose a multi-step ahead response time predictor for database queries based on a nonlinear autoregressive neural network model with exogenous inputs. The estimator shows many promising characteristics which make it a viable candidate for being implemented in admission control products for database servers. Performance of the proposed predictor is evaluated through experiments on a lab setup with a MySQL-server.

AB - Advanced telecommunication applications are often based on a multi-tier architecture, with application servers and database servers. With a rapidly increasing development of cloud computing and data centers, characterizations of the dynamics for database servers during changing workloads will be a key factor for analysis and performance improvements in these applications. We propose a multi-step ahead response time predictor for database queries based on a nonlinear autoregressive neural network model with exogenous inputs. The estimator shows many promising characteristics which make it a viable candidate for being implemented in admission control products for database servers. Performance of the proposed predictor is evaluated through experiments on a lab setup with a MySQL-server.

U2 - 10.1109/ISDA.2011.6121757

DO - 10.1109/ISDA.2011.6121757

M3 - Paper in conference proceeding

SN - 978-1-4577-1676-8

SP - 813

EP - 818

BT - [Host publication title missing]

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th International Conference on Intelligent Systems Design and Applications

Y2 - 22 November 2011 through 24 November 2011

ER -

NARX-based multi-step ahead response time prediction for database servers

Abstract

Publication series

Conference

Bibliographical note

Subject classification (UKÄ)

Access to Document

Fingerprint

Projects

LCCC

Cite this