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

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 pape...

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Main Authors: Wei Xiong, Bing Guo, Shen Yan
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Alexandria Engineering Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016821003136
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spelling doaj-dd01fda0ef1e4f8a90a3890cac65ca942021-07-31T04:37:31ZengElsevierAlexandria Engineering Journal1110-01682022-01-016117380Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliabilityWei Xiong0Bing Guo1Shen Yan2Computer Science College, Sichuan University, Chengdu 610064, China; Leshan Vocational & Technical College, Leshan 614000, ChinaComputer Science College, Sichuan University, Chengdu 610064, China; Corresponding author.School of Control Engineering, Chengdu University of Information Technology, Chengdu 610225, ChinaExecution 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.http://www.sciencedirect.com/science/article/pii/S1110016821003136Directed acrylic graph (DAG)Quantum particle swarm optimization (QPSO)Partial order relationsTime limitReliabilityEnergy consumption optimization
collection DOAJ
language English
format Article
sources DOAJ
author Wei Xiong
Bing Guo
Shen Yan
spellingShingle Wei Xiong
Bing Guo
Shen Yan
Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
Alexandria Engineering Journal
Directed acrylic graph (DAG)
Quantum particle swarm optimization (QPSO)
Partial order relations
Time limit
Reliability
Energy consumption optimization
author_facet Wei Xiong
Bing Guo
Shen Yan
author_sort Wei Xiong
title Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
title_short Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
title_full Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
title_fullStr Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
title_full_unstemmed Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
title_sort energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
publisher Elsevier
series Alexandria Engineering Journal
issn 1110-0168
publishDate 2022-01-01
description 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.
topic Directed acrylic graph (DAG)
Quantum particle swarm optimization (QPSO)
Partial order relations
Time limit
Reliability
Energy consumption optimization
url http://www.sciencedirect.com/science/article/pii/S1110016821003136
work_keys_str_mv AT weixiong energyconsumptionoptimizationofprocessorschedulingforrealtimeembeddedsystemsundertheconstraintsofsequentialrelationshipandreliability
AT bingguo energyconsumptionoptimizationofprocessorschedulingforrealtimeembeddedsystemsundertheconstraintsofsequentialrelationshipandreliability
AT shenyan energyconsumptionoptimizationofprocessorschedulingforrealtimeembeddedsystemsundertheconstraintsofsequentialrelationshipandreliability
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