@inproceedings{OklapiDeubzerSchmidhuberetal., author = {Oklapi, Erna and Deubzer, Michael and Schmidhuber, Stefan and Lalo, Erjola and Mottok, J{\"u}rgen}, title = {Optimization of Real-Time Multicore Systems Reached by a Genetic Algorithm Approach for Runnable Sequencing}, series = {2014 International Conference on Applied Electronics, Pilsen, Czech Republic}, booktitle = {2014 International Conference on Applied Electronics, Pilsen, Czech Republic}, doi = {10.1109/AE.2014.7011709}, pages = {233 -- 238}, abstract = {The deployment of complex real-time systems with everyday increasing demands and possibilities, is a challenging task for engineers when performance and efficiency have to be maximized while cost have to be minimized at the same time. For already designed systems it became necessary to perform different modifications in order to find optimal software architecture configuration by respecting all timing constraints which are essential when speaking of real-time systems. In this work, we present a model-based approach of optimizing the execution sequence of runnables within tasks in order to reduce the system's reaction times by improving the overall signal flow duration. Hereby, a genetic optimization algorithm is used to create and evaluate multiple solutions for the runnable sequencing problem. We conclude by demonstration the efficiency of the presented approach with experimental results.}, language = {en} } @inproceedings{OklapiDeubzerSchmidhuberetal., author = {Oklapi, Erna and Deubzer, Michael and Schmidhuber, Stefan and Mottok, J{\"u}rgen}, title = {Verification of an Evolutionary Optimization Algorithm for Runnable Sequencing Problem}, series = {4th Applied Research Conference, 5th July 2014, Ingolstadt}, booktitle = {4th Applied Research Conference, 5th July 2014, Ingolstadt}, language = {en} } @inproceedings{SailerSchmidhuberDeubzeretal., author = {Sailer, Andreas and Schmidhuber, Stefan and Deubzer, Michael and Alfranseder, Martin and Mucha, Matthias and Mottok, J{\"u}rgen}, title = {Optimizing the task allocation step for multi-core processors within autosar}, series = {2013 International Conference on Applied Electronics, IEEE, Pilsen, Czech Republic}, booktitle = {2013 International Conference on Applied Electronics, IEEE, Pilsen, Czech Republic}, abstract = {We present a model-based optimization approach for the task allocation problem in embedded multi-core systems. The information therefore is obtained from a system description in AUTOSAR and runtime measurements of the runnables in hardware traces. Based on this an initial software partitioning of runnables to tasks is created. We then use a genetic algorithm to create and evaluate solutions to the task allocation problem. Each solution is hereby evaluated using a discrete event-based simulation, which allows the evaluation with regard to real-time properties, resource consumption and data-communication overhead. The significance of our approach is then shown in a case-study. There, we optimize the task allocation of an embedded system, whose complexity is comparable to that of an actual system, on a multi-core processor. Finally, the results of the optimization are transferred to an ECU Configuration Description to enable further development in compliance with the AUTOSAR methodology.}, language = {en} } @inproceedings{MuchaMottokDeubzer, author = {Mucha, Matthias and Mottok, J{\"u}rgen and Deubzer, Michael}, title = {Probabilistic worst case response time estimation for multi-core real-time systems}, series = {2015 4th Mediterranean Conference on Embedded Computing (MECO), 14-18 June 2015, Budva, Montenegro}, booktitle = {2015 4th Mediterranean Conference on Embedded Computing (MECO), 14-18 June 2015, Budva, Montenegro}, pages = {31 -- 36}, abstract = {Traditional methods rely on Static Timing Analysis techniques to compute the Worst Case Response Time for tasks in real-time systems. Multi-Core real-time systems are faced up with concurrent task executions, semaphore accesses, and task migrations where it may be difficult to obtain the worst case upper bound. A new three staged probabilistic estimation concept is presented. Worst Case Response Times are estimated for tasksets which consist of tasks with multiple time bases. The concept involves data generation with sample classification and sample size equalization, model fit and Worst Case Response Time estimation on the basis of extreme value distribution models. A Generalized Pareto Distribution model fit method which includes threshold detection and parameter estimation is also presented. Sample classification in combination with the new Generalized Pareto Distribution model fit method allows to estimate Worst Case Response Times with low pessimism ranges compared to estimation methods that uses the Generalized Pareto or the Gumbel max distribution without sample classification.}, language = {en} } @inproceedings{SchmidhuberDeubzerMottok, author = {Schmidhuber, Stefan and Deubzer, Michael and Mottok, J{\"u}rgen}, title = {Genetic optimization of real-time multicore systems with respect to communication-based metrics}, series = {2nd Applied Research Conference 2012 (ARC 2012) 25./26. June 2012, Nuremberg}, booktitle = {2nd Applied Research Conference 2012 (ARC 2012) 25./26. June 2012, Nuremberg}, editor = {Mottok, J{\"u}rgen and Ziemann, Olaf}, publisher = {Shaker}, address = {Aachen}, isbn = {978-3-8440-1093-0}, pages = {21 -- 25}, language = {en} } @inproceedings{MartinSailerDeubzeretal., author = {Martin, Felix and Sailer, Andreas and Deubzer, Michael and Mottok, J{\"u}rgen}, title = {Automatische Multicore-Echtzeitvalidierung - Ein Prozess f{\"u}r modellbasierte Softwareentwicklung}, series = {Tagungsband 8th Embedded Software Engineering Kongress (ESE), 30.11. - 04.12.2015, Sindelfingen}, booktitle = {Tagungsband 8th Embedded Software Engineering Kongress (ESE), 30.11. - 04.12.2015, Sindelfingen}, language = {de} } @inproceedings{MartinSailerDeubzeretal., author = {Martin, Felix and Sailer, Andreas and Deubzer, Michael and Mottok, J{\"u}rgen}, title = {Automation of a Closed Loop Model-Based Development Process}, series = {Applied Research Conference 2015 (ARC 2015), 3rd July 2015, N{\"u}rnberg}, booktitle = {Applied Research Conference 2015 (ARC 2015), 3rd July 2015, N{\"u}rnberg}, language = {en} } @inproceedings{SailerDeubzerLuettgenetal., author = {Sailer, Andreas and Deubzer, Michael and L{\"u}ttgen, Gerald and Mottok, J{\"u}rgen}, title = {Comparing Trace Recordings of Automotive Realtime Software}, series = {RTNS '17: Proceedings of the 25th International Conference on Real-Time Networks and Systems, Grenoble, France, IEEE}, booktitle = {RTNS '17: Proceedings of the 25th International Conference on Real-Time Networks and Systems, Grenoble, France, IEEE}, doi = {10.1145/3139258.3139265}, pages = {118 -- 127}, abstract = {The process of engineering models of existing real-time system components is often difficult and time consuming, especially when legacy code has to be re-used or information about the exact timing behaviour is needed. In order to tackle this reverse engineering problem, we have developed the tool CoreTAna. CoreTAna derives an AUTOSAR compliant model of a real-time system by conducting dynamic analysis using trace recordings. Motivated by the challenge of assessing the quality of reverse engineered models of real-time software, we present a novel mathematical measure for comparing trace recordings from embedded real-time systems regarding their temporal behaviour. We also introduce a benchmark framework based on this measure, for evaluating reverse engineering tools such as CoreTAna. This considers common system architectures and also includes randomly generated systems and three systems of industrial automotive projects. Finally, an industrial case study demonstrates other use cases of our measure, such as impact analysis.}, language = {en} } @inproceedings{SailerDeubzerLuettgenetal., author = {Sailer, Andreas and Deubzer, Michael and L{\"u}ttgen, Gerald and Mottok, J{\"u}rgen}, title = {CoreTAna: A Trace Analyzer for Reverse Engineering Real-Time Software}, series = {IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER), March 14 to March 18 2016, Suita, Osaka, Japan}, booktitle = {IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER), March 14 to March 18 2016, Suita, Osaka, Japan}, doi = {10.1109/SANER.2016.36}, abstract = {With the availability of the AUTOSAR standard, model-driven methodologies are becoming established in theautomotive domain. However, the process of creating models ofexisting system components is often difficult and time consuming, especially when legacy code has to be re-used or informationabout the exact timing behavior is needed. In order to tackle thisreverse engineering problem, we present CoreTAna, a novel toolthat derives an AUTOSAR compliant model of a real-time systemfrom a dynamic analysis of its trace recordings. This paper givesan overview of CoreTAna's current features and discusses itsbenefits for reverse engineering.}, language = {en} }