Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability

• Published in: Alexandria engineering journal Vol. 61; no. 1; pp. 73 - 80
• Main Authors: Xiong, Wei, Guo, Bing, Yan, Shen
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2022; Elsevier
• Subjects: Directed acrylic graph (DAG); Energy consumption optimization; Partial order relations; Quantum particle swarm optimization (QPSO); Reliability; Time limit; Quantum particle swarm optimization (QPSO); Reliability; Time limit; Partial order relations; Energy consumption optimization; Directed acrylic graph (DAG)
• ISSN: 1110-0168; 2090-2670
• DOI: 10.1016/j.aej.2021.04.071

Execution time, reliability, and energy consumption are the three main performance parameters of processor scheduling for real-time embedded systems. It is very meaningful to optimize the energy optimization of processor scheduling to satisfy the requirements on time limit and reliability. This paper tries to optimize the energy consumption of the processor under three constraints: the partial ordering relations between task modules, the time limit, and the reliability. Based on directed acrylic graph (DAG) and quantum particle swarm optimization (QPSO), two scheduling algorithms were developed for the problem, namely, DAG_QPSO_I and DAG_QPSO_II. The two algorithms were compared with each other, and with other intelligent algorithms. The results show that the proposed algorithms are superior in optimization effect and efficiency, DAG_QPSO_I makes energy consumption more efficient than DAG_QPSO_II, and DAG_QPSO_II meets stricter requirements on time limit and reliability than DAG_QPSO_I.