Global Best-Case Response Time for Improving the Worst-Case Response Times in Distributed Real-Time Systems

Abstract : In this paper an improvement of the schedulability analysis for fixed-priority distributed hard real-time systems is presented. During the analysis it is not sufficient to include the tasks' worst-case execution time, but also the best-case execution time has to be considered, because the lower bound of the execution has a direct impact on the event densities in the system. The presented approach improves the best-case response time analysis introduced by Redell et al. The paper shows how it is possible to calculate a lower bound for the best-case response time using an expressive event model. This new lower bound of the response time will relax the event densities in a distributed system and will therefore lead to more relaxed worst-case response times.
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Communication dans un congrès
Mike Hinchey; Bernd Kleinjohann; Lisa Kleinjohann; Peter A. Lindsay; Franz J. Rammig; Jon Timmis; Marilyn Wolf. 7th IFIP TC 10 Working Conference on Distributed, Parallel and Biologically Inspired Systems (DIPES) / 3rd IFIP TC 10 International Conference on Biologically-Inspired Collaborative Computing (BICC) / Held as Part of World Computer Congress (WCC) , Sep 2010, Brisbane, Australia. Springer, IFIP Advances in Information and Communication Technology, AICT-329, pp.157-168, 2010, Distributed, Parallel and Biologically Inspired Systems. 〈10.1007/978-3-642-15234-4_16〉
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Steffen Kollmann, Victor Pollex, Frank Slomka. Global Best-Case Response Time for Improving the Worst-Case Response Times in Distributed Real-Time Systems. Mike Hinchey; Bernd Kleinjohann; Lisa Kleinjohann; Peter A. Lindsay; Franz J. Rammig; Jon Timmis; Marilyn Wolf. 7th IFIP TC 10 Working Conference on Distributed, Parallel and Biologically Inspired Systems (DIPES) / 3rd IFIP TC 10 International Conference on Biologically-Inspired Collaborative Computing (BICC) / Held as Part of World Computer Congress (WCC) , Sep 2010, Brisbane, Australia. Springer, IFIP Advances in Information and Communication Technology, AICT-329, pp.157-168, 2010, Distributed, Parallel and Biologically Inspired Systems. 〈10.1007/978-3-642-15234-4_16〉. 〈hal-01054478〉

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