Heterogeneous multi-core task scheduling based on adaptive simulated annealing

doi:10.23919/JSEE.2026.000042

Abstract

Abstract:

To address the energy consumption issues caused by task lengths in task scheduling on heterogeneous multi-core systems, this paper proposes an adaptive parameterized improved simulated annealing algorithm based on the directed acyclic graph task model. The algorithm employs feedback from acceptance rates to dynamically adjust the temperature and neighborhood size of the simulated annealing process. Additionally, it introduces a security mechanism to enhance convergence speed and global search capabilities. Compared against classical simulated annealing and standard heuristic algorithms, the proposed algorithm achieves reductions exceeding 54% in convergence generations, 50% in task slots, and 10% in scheduling time, providing a direction for low-power task scheduling.

Key words: heterogeneous multi-core, task scheduling, schedule length, simulated annealing

Guoliang ZHU, Jinjian ZHANG, Xuan LIU, Guojun WANG, Xiaodong ZHANG, Kaiyu CHEN, Yu WANG. Heterogeneous multi-core task scheduling based on adaptive simulated annealing[J]. Journal of Systems Engineering and Electronics, 2026, 37(3): 897-903.

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Algorithm	0	1	2	3	4
SA	213.5	317.3	369.2	153.4	363.8
ASA	158.1	255.9	327.3	106.6	304.1

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