Abstract
This paper deals with the task placement problem for real-time systems on heterogeneous processors. Indeed, the task placement phase must ensure, on the one hand, that the temporal properties are respected while also being optimal in terms of meeting their limited resources. We propose in this paper an optimization-based strategy to investigate how tasks are assigned to processors in order to solve this issue. We suggest a formulation for a multi-objective evolution approach that maximizes the system’s extensibility while minimizing energy consumption. The proposed approach enables designers to investigate the search space of all potential task to processor assignments and identify schedulable solutions that offer excellent trade-offs between the two optimization objectives. We first describe the mapping approach and then offer a series of experiments to test the effectiveness of the proposed model.
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Lassoued, R., Mzid, R. (2023). A Multi-objective Evolution Strategy for Real-Time Task Placement on Heterogeneous Processors. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-031-35501-1_45
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DOI: https://doi.org/10.1007/978-3-031-35501-1_45
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