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Quantifying and Suppressing the Measurement Disturbance in Feedback Controlled Real-Time Systems
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA, USA.
University of Virginia, USA.
2008 (English)In: Real-time systems, ISSN 0922-6443, E-ISSN 1573-1383, Vol. 40, no 1, 44-76 p.Article in journal (Refereed) Published
Abstract [en]

In the control of continuous and physical systems, the controlled system is sampled sufficiently fast to capture the dynamics of the system. In general, this property cannot be applied to the control of computer systems as the measured variables are often computed over a data set, e.g., deadline miss ratio. In this paper we quantify the disturbance present in the measured variable as a function of the data set size and the sampling period, and we propose a feedback control structure that suppresses the measurement disturbance. The experiments we have carried out show that a controller using the proposed control structure outperforms a traditional control structure with regard to performance reliability.

Place, publisher, year, edition, pages
Springer, 2008. Vol. 40, no 1, 44-76 p.
Keyword [en]
Adaptive scheduling, Feedback control, Measurement disturbance, System disturbance
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-12639DOI: 10.1007/s11241-008-9048-3OAI: diva2:16752
Available from: 2007-10-17 Created: 2007-10-17 Last updated: 2013-07-22
In thesis
1. QoS Control of Real-Time Data Services under Uncertain Workload
Open this publication in new window or tab >>QoS Control of Real-Time Data Services under Uncertain Workload
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Real-time systems comprise computers that must generate correct results in a timely manner. This involves a wide spectrum of computing systems found in our everyday life ranging from computers in rockets to our mobile phones. The criticality of producing timely results defines the different types of realtime systems. On one hand, we have the so-called hard real-time systems, where failing to meet deadlines may result in a catastrophe. In this thesis we are, however, concerned with firm and soft real-time systems, where missing deadlines is acceptable at the expense of degraded system performance. The usage of firm and soft real-time systems has increased rapidly during the last years, mainly due to the advent of applications in multimedia, telecommunication, and e-commerce. These systems are typically data-intensive, with the data normally spanning from low-level control data, typically acquired from sensors, to high-level management and business data. In contrast to hard real-time systems, the environments in which firm and soft real-time systems operate in are typically open and highly unpredictable. For example, the workload applied on a web server or base station in telecommunication systems varies according to the needs of the users, which is hard to foresee. In this thesis we are concerned with quality of service (QoS) management of data services for firm and soft real-time systems. The approaches and solutions presented aim at providing a general understanding of how the QoS can be guaranteed according to a given specification, even if the workload varies unpredictably. The QoS specification determines the desired QoS during normal system operation, and the worst-case system performance and convergence rate toward the desired setting in the face of transient overloads. Feedback control theory is used to control QoS since little is known about the workload applied on the system. Using feedback control the difference between the measured QoS and the desired QoS is formed and fed into a controller, which computes a change to the operation of the real-time system. Experimental evaluation shows that using feedback control is highly effective in managing QoS such that a given QoS specification is satisfied. This is a key step toward automatic management of intricate systems providing real-time data services.

Place, publisher, year, edition, pages
Institutionen för datavetenskap, 2007. 244 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1143
real-time system, database, feedback control
National Category
Computer Science
urn:nbn:se:liu:diva-10016 (URN)978-91-85895-49-6 (ISBN)
Public defence
2007-11-15, Planck, Fysikhuset, Linköpings universitet, 13:15 (English)
Available from: 2007-10-17 Created: 2007-10-17 Last updated: 2009-04-22

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Amirijoo, MehdiGunnarsson, SvanteHansson, Jörgen
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