[1]于国龙,崔忠伟,左 羽.基于离散粒子群优化的MPSoC节能调度算法[J].江西师范大学学报(自然科学版),2016,40(03):307-311.
 YU Guolong,CUI Zhongwei,ZUO Yu.MPSoC Energy Saving Scheduling Algorithm Based on Discrete Particle Swarm Optimization[J].,2016,40(03):307-311.
点击复制

基于离散粒子群优化的MPSoC节能调度算法()
分享到:

《江西师范大学学报》(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2016年03期
页码:
307-311
栏目:
出版日期:
2016-07-01

文章信息/Info

Title:
MPSoC Energy Saving Scheduling Algorithm Based on Discrete Particle Swarm Optimization
作者:
于国龙崔忠伟左 羽
贵州师范学院数学与计算机科学学院,贵州省高校工业物联网工程技术研究中心,贵州 贵阳 550018
Author(s):
YU GuolongCUI ZhongweiZUO Yu
School of Mathematics and Computer Science,Guizhou Province University Industrial Networking Engineering Technology Research Center,Guizhou Normal College,Guiyang Guizhou 550018,China
关键词:
粒子群算法 多处理器片上系统 节能 调度算法
Keywords:
particle swarm optimization MPSoC energy saving scheduling algorithm
分类号:
TP 302.1
文献标志码:
A
摘要:
为了降低多核片上系统MPSoC在应用中的能耗,在MPSoC上提出了基于优化离散粒子群算法的节能任务调度算法.通过比例选择算子生成初始种群,以任务在MPSoC上不同内核执行的能耗作为解空间,粒子群在整个解空间上搜索最低能耗调度方案,并在算法中优化了粒子群算法的局部早熟问题,使算法性能进一步提升.仿真实验表明:基于优化离散粒子群算法的节能调度算法与常用的3种调度算法相比,能耗得到了降低,且算法的截止期错失率并没有升高,保证了算法的整体性能.
Abstract:
In order to reduce the energy consumption of the MPSoC in the application,a energy saving task scheduling algorithm based on the optimization of discrete particle swarm optimization is proposed in MPSoC.The algorithm generates the initial population by the proportional selection operator,and takes the energy consumption of different cores on the MPSoC as the solution space,search for the lowest energy consumption scheduling scheme in the whole solution space and optimize local premature problem of the particle swarm optimization algorithm.Through these improve the performance of the algorithm.The simulation experiments show that the energy of saving scheduling algorithm based on the optimized discrete particle swarm optimization algorithm is lower than that of the common three algorithms,and the deadline miss rate of the algorithm does not increase,that ensure the overall performance of the algorithm.

参考文献/References:

[1] 叶常华,左朝树.基于多核处理器的节能任务调度方法 [J].中国电子科学研究院学报,2012,7(2):204-207.
[2] Mei Jing,Li Kenli,Hu Jingtong,et al.Energy-aware preemptive scheduling algorithm for sporadic tasks on DVS platform [J].Microprocessors and Microsystems,2013,37(1):99-112.
[3] 葛永琪,董云卫,张健,等.一种能量收集嵌入式系统自适应调度算法 [J].软件学报,2015,26(4):819-834.
[4] Huang Kai,Wolfgang Haid,Iuliana Bacivarov,et al.Embedding formal performance analysis into the design cycle of MPSoCs for real-time streaming applications [J].ACM Transactions on Embedded Computing Systems,2012(1):135-151.
[5] Tavakkoli-Moghaddam R,Azarkish M,Sadeghnejad Barkousaraie A.A new hybrid multi-objective pareto archive PSO algorithm for a bi-objective job shop scheduling problem [J].Expert Systems With Applications,2011,38(9):10812-10821.
[6] 成洪甲,杨雨,孙寅萍.一种基于随机粒子群的变差函数优化方法 [J].科学技术与工程,2012,12(31):8374-8378.
[7] Gao Xiang,Chen Yunji,Wang Huandong,et al.System architecture of Godson-3 multi-core processors [J].Journal of Computer Science and Technology,2010,25(2):181-191.
[8] Zhang Guojun,Liu Min,Li Jian,et al.Multi-objective optimization for surface grinding process using a hybrid particle swarm optimization algorithm [J].The International Journal of Advanced Manufacturing Technology,2014,71(9/12):1861-1872.
[9] Fariborz Jolai,Reza Tavakkoli-Moghaddam,Mohammad Taghipour.A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations [J].International Journal of Production Research,2012,50(15):4279-4293.
[10] Liao Chingjong,Evi Tjandradjaja,Chung Tsui Ping.An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem [J].Applied Soft Computing Journal,2012,12(6):1755-1764.
[11] Li Jia,Cheng Dashuai,Chiu Minsen.Pareto-optimal solutions based multi-objective particle swarm optimization control for batch processes [J].Neural Computing and Applications,2012,21(6):1107-1116.
[12] Hasan Hosseini-Nasab,Leila Emami.A hybrid particle swarm optimisation for dynamic facility layout problem [J].International Journal of Production Research,2013(14):4325-4335.
[13] Shieh Wann Yun,Pong Chin Ching.Energy and transition-aware runtime task scheduling for multicore processors [J].Journal of Parallel and Distributed Computing,2013,73(9):1225-1238.
[14] Boris Shnits.Multi-criteria optimisation-based dynamic scheduling for controlling FMS [J].International Journal of Production Research,2012,50(21):1-11.
[15] 赵振江.基于量子粒子群优化算法的 PID 参数控制[J].科学技术与工程,2012,12(22):5490-5492.
[16] Krishnamoorthy M,Ernst A T,Baatar D.Algorithms for large scale shift minimisation personnel task scheduling problems [J].European Journal of Operational Research,2011,219(1):34-48.
[17] Huang Kai,Santinelli L,Chen Jianjia,et al.Applying real-time interface and calculus for dynamic power management in hard real-time systems [J].Real Time Systems,2011,47(2):163-193.
[18] Abusayeed Saifullah,Li Jing,Kunal Agrawal,et al.Multi-core real-time scheduling for generalized parallel task models [J].Real Time Systems,2013,49(4):404-435.

相似文献/References:

[1]张兴国,周东健,李成浩.基于粒子群-蚁群融合算法的移动机器人路径优化规划[J].江西师范大学学报(自然科学版),2014,(03):274.
 ZHANG Xing-guo,ZHOU Dong-jian,LI Cheng-hao.The Optimal Path Planning for Mobile Robot Based on Ant Colony Algorithm Combined with Particle Swarm Optimization[J].,2014,(03):274.

备注/Memo

备注/Memo:
收稿日期:2016-02-13基金项目:贵州省2014年省级本科教学工程项目(黔教高发〔2014〕378)和2015年省级本科教学工程建设项目(黔教高发〔2015〕337)和卓越工程师教育培养计划(黔教高发〔2013〕446)资助项目.作者简介:于国龙(1981-),男,辽宁东港人,讲师,主要从事物联网和大数据的研究.
更新日期/Last Update: 1900-01-01