Real-time scheduling in heterogeneous systems considering cache reload time using genetic algorithms

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Abstract

Since optimal assignment of tasks in a multiprocessor system is, in almost all practical cases, an NP-hard problem, in recent years some algorithms based on genetic algorithms have been proposed. Some of these algorithms have considered real-time applications with multiple objectives, total tardiness, completion time, etc. Here, we propose a suboptimal static scheduler of nonpreemptable tasks in hard real-time heterogeneous multiprocessor systems considering time constraints and cache reload time. The approach makes use of genetic algorithm to minimize total completion time and number of processors used, simultaneously. One important issue which makes this research different from previous ones is cache reload time. The method is implemented and the results are compared against a similar method.

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Miryani, M. R., & Naghibzadeh, M. (2009). Real-time scheduling in heterogeneous systems considering cache reload time using genetic algorithms. In IFIP Advances in Information and Communication Technology (Vol. 310, pp. 115–126). Springer New York LLC. https://doi.org/10.1007/978-3-642-04284-3_11

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