Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/240017

Title

Managing performance and resources in software systems using nonlinear predictive control

Author(s)

Patikirikorala, Tharindu;  Wang, Liuping;  Colman, Alan;  Han, Jun

Abstract

Management of quality of service performance and resources in a shared resource environment is vital to many business domains to achieve business objectives. These management systems provide agreed levels of quality of service to their clients while allocating limited available resources among them. It is well known that the behavior of such software systems illustrate nonlinear characteristics, imposing difficulties to model and control the system. This paper proposes a nonlinear model predictive control technique for managing the performance and resources in such a shared resource environment. In particular, a block-oriented Wiener model is utilized to represent the software system as a multi-input and multi-output model in series with static nonlinear components at the outputs. Then a predictive control system is designed by compensating the estimated nonlinearities with their inverse. The simulation results show that the proposed nonlinear model predictive control mechanism has significantly improved the performance and resource management at runtime over the linear predictive control counterpart.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies

Source

Proceedings of the 2012 American Control Conference (ACC 2012), Montreal, Canada, 27-29 June 2012, pp. 4124-4129

Publication year

2012

Keyword(s)

Predictive control;  Resources;  Service performance;  Shared resource environment;  Software systems

Publisher

IEEE

ISSN

0743-1619 (series ISSN)

ISBN

9781457710957, 1457710951

Publisher URL

http://ieeexplore.ieee.org/

Copyright

Copyright © 2012 AACC.

Peer reviewed