| Citation: | Jun LUO, Zewei LIU, Ping ZHAGN, Xueming LIU, Zheng LIU. Application of Improved Bird Swarm Algorithm Based on Nonlinear Factor in Dynamic Energy Management[J]. Journal of Electronics & Information Technology, 2020, 42(3): 729-736. doi: 10.11999/JEIT190264
|
The application of Dynamic Voltage Scaling (DVS) technique in real-time system energy management will result in the decrease of system reliability. A dynamic energy management method based on Improved Bird Swarm Algorithm (IoBSA) is proposed in this paper. Firstly, the population is initialized uniformly with the principle of good point set, so as to improve the quality of initial solution and increase the diversity of population effectively. Secondly, in order to balance better the global and local search ability of BSA algorithm, the nonlinear dynamic adjustment factor is proposed. Then, a power consumption model with time and reliability constraints is established for the dynamic adjustment of processor frequency in embedded real-time systems. On the premise of ensuring real-time performance and stability, the proposed IoBSA algorithm is used to find the solution with minimum energy consumption. The experimental results show that compared with the traditional BSA algorithm and other common algorithms, the improved bird swarm algorithm has a strong advantage in solving the minimum energy consumption and a fast processing speed energy management.
|
SALEHI M E, SAMADI M, NAJIBI M, et al. Dynamic voltage and frequency scheduling for embedded processors considering power/performance tradeoffs[J]. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2011, 19(10): 1931–1935. doi: 10.1109/tvlsi.2010.2057520
|
|
TERZOPOULOS G and KARATZA H. Performance evaluation and energy consumption of a real-time heterogeneous grid system using DVS and DPM[J]. Simulation Modelling Practice and Theory, 2013, 36: 33–43. doi: 10.1016/j.simpat.2013.04.006
|
|
ERNST D, DAS S, LEE S, et al. Razor: Circuit-level correction of timing errors for low-power operation[J]. IEEE Micro, 2004, 24(6): 10–20. doi: 10.1109/MM.2004.85
|
|
RONG Peng, PEDRAM M. Energy-aware task scheduling and dynamic voltage scaling in a real-time system[J]. Journal of Low Power Electronics, 2008, 4(1): 1–10. doi: 10.1166/jolpe.2008.154
|
|
韩文雅, 王雷. 基于混合任务模型的动态电压调度在无线传感器网络中的应用[J]. 计算机应用, 2010, 30(9): 2522–2525. doi: 10.3724/SP.J.1087.2010.02522
HAN Wenya and WANG Lei. Application of dynamic voltage scaling based on hybrid-task model in wireless sensor network[J]. Journal of Computer Applications, 2010, 30(9): 2522–2525. doi: 10.3724/SP.J.1087.2010.02522
|
|
ZHAO Baoxian, AYDIN H, and ZHU Dakai. On maximizing reliability of real-time embedded applications under hard energy constraint[J]. IEEE Transactions on Industrial Informatics, 2010, 6(3): 316–328. doi: 10.1109/tii.2010.2051970
|
|
晏福, 徐建中, 李奉书. 混沌灰狼优化算法训练多层感知器[J]. 电子与信息学报, 2019, 41(4): 872–879. doi: 10.11999/JEIT180519
YAN Fu, XU Jianzhong, and LI Fengshu. Training multi-layer perceptrons using chaos grey wolf optimizer[J]. Journal of Electronics &Information Technology, 2019, 41(4): 872–879. doi: 10.11999/JEIT180519
|
|
张兴明, 殷从月, 魏帅, 等. 基于双仲裁机制和田口正交法的猫群优化任务调度算法[J]. 电子与信息学报, 2018, 40(10): 2521–2528. doi: 10.11999/JEIT180215
ZHANG Xingming, YIN Congyue, WEI Shuai, et al. Cat swarm optimization task scheduling algorithm based on double arbitration mechanism and Taguchi orthogonal method[J]. Journal of Electronics &Information Technology, 2018, 40(10): 2521–2528. doi: 10.11999/JEIT180215
|
|
肖乐意, 欧阳红林, 范朝冬. 基于记忆分子动理论优化算法的多目标截面投影Otsu图像分割[J]. 电子与信息学报, 2018, 40(1): 189–199. doi: 10.11999/JEIT170301
XIAO Leyi, OUYANG Honglin, and FAN Chaodong. Multi-objective cross section projection Otsu's method based on memory knetic-molecular theory optimization algorithm[J]. Journal of Electronics &Information Technology, 2018, 40(1): 189–199. doi: 10.11999/JEIT170301
|
|
罗钧, 刘永锋, 付丽. 能耗限制的实时周期任务可靠性感知调度[J]. 重庆大学学报, 2011, 34(8): 86–89. doi: 10.11835/j.issn.1000-582x.2011.08.015
LUO Jun, LIU Yongfeng, and FU Li. Reliability-aware schedule of periodic tasks in energy-constrained real-time systems[J]. Journal of Chongqing University, 2011, 34(8): 86–89. doi: 10.11835/j.issn.1000-582x.2011.08.015
|
|
MENG Xianbing, GAO X Z, LU Lihua, et al. A new bio-inspired optimisation algorithm: bird swarm algorithm[J]. Journal of Experimental & Theoretical Artificial Intelligence, 2016, 28(4): 673–687. doi: 10.1080/0952813X.2015.1042530
|
|
杨文荣, 马晓燕, 边鑫磊. 基于Levy飞行策略的自适应改进鸟群算法[J]. 河北工业大学学报, 2017, 46(5): 10–16. doi: 10.14081/j.cnki.hgdxb.2017.05.002
YANG Wenrong, MA Xiaoyan, and BIAN Xinlei. Adaptive improved bird swarm algorithm based on Levy flight strategy[J]. Journal of Hebei University of Technology, 2017, 46(5): 10–16. doi: 10.14081/j.cnki.hgdxb.2017.05.002
|
|
李延延, 万仁霞. 一种改进算的鸟群算法[J]. 微电子学与计算机, 2018, 35(9): 79–84.
LI Yanyan and WAN Renxia. An improved algorithm for bird swarm optimization[J]. Microelectronics &Computer, 2018, 35(9): 79–84.
|
|
吴军, 王龙龙. 基于双鸟群混沌优化的Otsu图像分割算法[J]. 微电子学与计算机, 2018, 35(12): 119–124. doi: 10.19304/j.cnki.issn1000-7180.2018.12.024
WU Jun and WANG Longlong. An Otsu image segmentation algorithm based on chaos optimization of two BSA[J]. Microelectronics &Computer, 2018, 35(12): 119–124. doi: 10.19304/j.cnki.issn1000-7180.2018.12.024
|
|
王进成, 高岳林. 基于改进的鸟群算法求解农产品冷链物流配送路径优化问题[J]. 安徽农业科学, 2018, 46(25): 1–4. doi: 10.13989/j.cnki.0517-6611.2018.25.001
WANG Jincheng and GAO Yuelin. Optimization problem of cold chain logistics distribution path of agricultural products based on improved algorithm of bird swarm optimization[J]. Journal of Anhui Agricultural Sciences, 2018, 46(25): 1–4. doi: 10.13989/j.cnki.0517-6611.2018.25.001
|
|
谢国民, 干毅军, 丁会巧. 基于佳点集的蝙蝠定位算法在WSN中应用[J]. 传感技术学报, 2017, 30(8): 1252–1257. doi: 10.3969/j.issn.1004-1699.2017.08.021
XIE Guomin, GAN Yijun, and DING Huiqiao. A positioning algorithm based on bat algorithm and good-point setsin the application of WSN[J]. Chinese Journal of Sensors and Actuators, 2017, 30(8): 1252–1257. doi: 10.3969/j.issn.1004-1699.2017.08.021
|
|
ZHU D, MELHEM R, and CHILDERS B. Scheduling with dynamic voltage/speed adjustment using slack reclamation in multi-processor real-time systems[C]. Proceedings of the 22nd IEEE Real-time Systems Symposium, London, UK, 2001: 84–94.
|
|
SHEHAB M, KHADER A T, LAOUCHEDI M, et al. Hybridizing cuckoo search algorithm with bat algorithm for global numerical optimization[J]. The Journal of Supercomputing, 2019, 75(5): 2395–2422. doi: 10.1007/s11227-018-2625-x
|
|
MIRJALILI S, MIRJALILI S M, and LEWIS A. Grey wolf optimizer[J]. Advances in Engineering Software, 2014, 69: 46–61. doi: 10.1016/j.advengsoft.2013.12.007
|
|
罗钧, 杨永松, 侍宝玉. 基于改进的自适应差分演化算法的二维Otsu多阈值图像分割[J]. 电子与信息学报, 2019, 41(8): 2017–2024. doi: 10.11999/JEIT180949
LUO Jun, YANG Yongsong, and SHI Baoyu. multi-threshold image segmentation of 2D Otsu based on improved adaptive differential evolution algorithm[J]. Journal of Electronics &Information Technology, 2019, 41(8): 2017–2024. doi: 10.11999/JEIT180949
|
Figures(3) / Tables(5)
DownLoad:
