电子测量与仪器学报

罗钧,庞亚男,刘建强.基于历史认知的鲸鱼算法求解动态能耗[J].电子测量与仪器学报,2022,36(1):236-245

基于历史认知的鲸鱼算法求解动态能耗

Whale algorithm based on historical cognition forsolving dynamic energy consumption

DOI：

英文关键词:energy consumption management dynamic voltage scaling historical cognition nonlinear convergence factor improved whale algorithm

基金项目:国防科工局十二五技术基础科研项目(JSJL2014209B005)、工信部“两机”重大专项基础研究项目(Z20210208)资助

作者	单位
罗钧	1. 重庆大学光电技术及系统教育部重点实验室
庞亚男	1. 重庆大学光电技术及系统教育部重点实验室，2. 四川航天电子设备研究所
刘建强	1. 重庆大学光电技术及系统教育部重点实验室

Author	Institution
Luo Jun	1. Key Laboratory of Optoelectronic Technology and System of Ministry of Education, Chongqing University
Pang Yanan	1. Key Laboratory of Optoelectronic Technology and System of Ministry of Education, Chongqing University,2. Sichuan Aerospace Electronic Equipment Research Institute
Liu Jianqiang	1. Key Laboratory of Optoelectronic Technology and System of Ministry of Education, Chongqing University

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中文摘要:

为提高嵌入式实时系统的能耗管理效率,降低传统动态电压缩放对系统稳定性的影响,提出了基于历史认知的鲸鱼算法支持下的动态能耗优化方案。首先提出非线性动态控制收敛因子的策略,有效加快了算法收敛速度。其次采用历史最优解作为收缩包围机制中的种群干扰因子,设计了混合引导策略来平衡算法的局部开发和全局搜索能力。最后根据动态电压缩放技术可以实时改变处理器频率的特征,利用改进算法对任务量 10、30 和 50 进行优化,验证了改进算法的有效性。

英文摘要:

In order to improve the energy consumption management efficiency of the embedded real-time system and reduce the impact of traditional dynamic voltage scaling technology on system stability, a dynamic energy consumption optimization scheme supported by whale algorithm based on historical cognition is proposed. Firstly, a nonlinear dynamic convergence factor control strategy is proposed, which can effectively accelerate the convergence speed of the algorithm. Secondly, using the historical optimum solutions as interference factors, a hybrid guided strategy is designed in the constriction and envelopment mechanism to balance the local development and global search capability of the algorithm. Finally, the frequency characteristics of the processor can be changed in real time according to the dynamic voltage scaling technology, the tasks 10, 30 and 50 are optimized by the algorithm, so as to verify the effectiveness of the improved algorithm.

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