@inproceedings{LaloDeubzerSchmidhuberetal., author = {Lalo, Erjola and Deubzer, Michael and Schmidhuber, Stefan and Oklapi, Erna and Mottok, J{\"u}rgen}, title = {Task Priority Optimization in Real-Time Multi-Core Embedded Systems}, series = {4. Landshuter Symposium Mikrosystemtechnik, Mikrosystemtechnik als Schl{\"u}sseltechnologie der Systemintegration, Tagungsband zum Symposium 12./13. M{\"a}rz 2014, Hochschule Landshut}, booktitle = {4. Landshuter Symposium Mikrosystemtechnik, Mikrosystemtechnik als Schl{\"u}sseltechnologie der Systemintegration, Tagungsband zum Symposium 12./13. M{\"a}rz 2014, Hochschule Landshut}, address = {Landshut}, isbn = {978-3-9812696-5-9}, pages = {96 -- 109}, abstract = {The shift from single-core to multi-core processors in real-time embedded systems leads to communication based effects on timing such as inter-core communication delays and blocking times. Moreover, the complexity of the scheduling problem increases when multi-core processors are used. In priority-based-scheduling, a fixed priority assignment is used in order to enable predictable behavior of the system. Predictability means that the system has to be analyzable which allows the detection of problems coming from scheduling decisions. For fixed priority scheduling in multi-core real-time embedded systems, a proper task priority assignment has to be done in a way that the system has minimal effects on timing. In this paper, we present an approach for finding near-optimal solutions for task priority assignment and the preemption/cooperation problem. A genetic algorithm is hereby used to create priority assignment solutions. A timing simulator is used for evaluation of each solution regarding real-time properties, memory consumption and communication overhead. In a case study we demonstrate that the proposed approach performs better than well known and single-core optimal heuristics for relatively complex systems.}, language = {de} } @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} }