Abstract
In this paper we present a method of synthesis of adaptive schedulers for power aware real-time embedded software. We assume that the system is specified as a task graph, which should be scheduled on multi-core embedded processor with low-power processing capabilities. First, the developmental genetic programming is used to generate the scheduler and the initial schedule. The scheduler and the initial schedule are optimized taking into consideration power consumption as well as self-adaptivity capabilities. During the system execution the scheduler modifies the schedule whenever execution time of the recently finished task occurred shorter or longer than expected. The goal of rescheduling is to minimize the power consumption while all time constraints will be satisfied. We present real-life example as well as some experimental results showing advantages of our method.
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Deniziak, S., Ciopiński, L. (2016). Synthesis of Power Aware Adaptive Embedded Software Using Developmental Genetic Programming. In: Fidanova, S. (eds) Recent Advances in Computational Optimization. Studies in Computational Intelligence, vol 655. Springer, Cham. https://doi.org/10.1007/978-3-319-40132-4_7
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DOI: https://doi.org/10.1007/978-3-319-40132-4_7
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