Abstract
Today’s embedded systems representatively feature computing resource constraints as well as workload uncertainty. This gives rise to the increasing demand of integrating control and scheduling in control applications that are built upon embedded systems. To address the impact of uncertain computing resource availability on quality of control (QoC), an intelligent control theoretic approach to feedback scheduling is proposed based on fuzzy logic control technology. The case with one single control task that competes for CPU resources with other non-control tasks is considered. The sampling period of the control task is dynamically adjusted. The goal is to provide runtime adaptation and flexible QoC management in the presence of CPU resource constraint and workload uncertainty. Preliminary simulation results argue that the fuzzy feedback scheduler is effective in managing QoC in real-time embedded control applications.
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Xia, F., Liu, L., Sun, Y. (2005). Flexible Quality-of-Control Management in Embedded Systems Using Fuzzy Feedback Scheduling. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_66
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DOI: https://doi.org/10.1007/11548706_66
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