Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/82708
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Type: Conference paper
Title: Model-driven performance prediction of distributed real-time embedded defence systems
Author: Falkner, K.
Chiprianov, V.
Falkner, N.
Szabo, C.
Hill, J.
Puddy, G.
Fraser, D.
Johnston, A.
Rieckmann, M.
Wallis, A.
Citation: Proceedings, 2013 International Conference on Engineering of Complex Computer Systems, ICECCS 2013, 17–19 July 2013, Singapore: pp.155-158
Publisher: IEEE
Publisher Place: USA
Issue Date: 2013
Series/Report no.: IEEE International Conference on Engineering of Complex Computer Systems-ICECCS
ISBN: 9780769550077
ISSN: 2770-8527
2770-8535
Conference Name: International Conference on Engineering of Complex Computer Systems (18th : 2013 : Singapore)
Statement of
Responsibility: 
Katrina Falkner, Vanea Chiprianov, Nickolas J.G. Falkner, Claudia Szabo, James H. Hill, Gavin Puddy, Dan Fraser, Adrian Johnston, Marianne Rieckmann, Andrew Wallis
Abstract: Autonomous defence systems are typically characterised by hard constraints on space, weight and power. These constraints have a strong impact on the non-functional properties, and performance, of the final system. System execution modelling tools permit early prediction of the performance of model driven systems, however the focus to date has been on understanding the performance of a model rather than determining if it meets performance requirements, and subsequently carrying out analysis to reveal the causes of any requirement violations. In this paper, we propose an integrated approach to performance prediction of model-driven distributed real time embedded defence systems. Our architectural prototyping system supports a scenario-driven experimental platform for evaluating model suitability within a set of deployment and real-time performance constraints. We present an overview of our performance prediction system, demonstrating the integration of modelling, execution and visualisation, and discuss a case study to illustrate our approach.
Rights: © 2013 IEEE
DOI: 10.1109/ICECCS.2013.29
Published version: http://dx.doi.org/10.1109/iceccs.2013.29
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Computer Science publications

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