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Experimental Evaluation of Linear Time-Invariant Models for Feedback Performance Control in 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 Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology.
University of Virginia, USA.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2007 (English)In: Real-time systems, ISSN 0922-6443, E-ISSN 1573-1383, Vol. 35, no 3, 209-238 p.Article in journal (Refereed) Published
Abstract [en]

In recent years a new class of soft real-time applications operating in unpredictable environments has emerged. Typical for these applications is that neither the resource requirements nor the arrival rates of service requests are known or available a priori. It has been shown that feedback control is very effective to support the specified performance of dynamic systems that are both resource insufficient and exhibit unpredictable workloads. To efficiently use feedback control scheduling it is necessary to have a model that adequately describes the behavior of the system. In this paper we experimentally evaluate the accuracy of four linear time-invariant models used in the design of feedback controllers. We introduce a model (DYN) that captures additional system dynamics, which a previously published model (STA) fails to include. The accuracy of the models are evaluated by validating the models with regard to measured data from the controlled system and through a set of experiments where we evaluate the performance of a set of feedback control schedulers tuned using these models. From our evaluations we conclude that second order models (e.g., DYN) are more accurate than first order models (e.g. STA). Further we show that controllers tuned using second order models perform better than controllers tuned using first order models.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2007. Vol. 35, no 3, 209-238 p.
Keyword [en]
Feedback control scheduling, Modeling, Model validation, System identification
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-12636DOI: 10.1007/s11241-006-9008-8OAI: diva2:16749
Available from: 2007-10-17 Created: 2007-10-17 Last updated: 2013-07-21
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, MehdiHansson, JörgenGunnarsson, Svante
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