期刊文献+

FTT调度模型中面向性能优化的消息周期指定算法

Messages Period Assignment Algorithm Oriented to Performance Optimization in Flexible Time-triggered Scheduling Model
下载PDF
导出
摘要 针对周期可变的实时消息集,建立柔性时间触发调度模型下消息周期与系统性能的优化模型,并给出解析取整和贪心选择2种消息周期近似最优指定算法。在此基础上,提出结合OptInt与Greed 2种算法的Comb算法。Comb算法通过利用OptInt算法获得较好的初始解,运用Greed算法对初始解进行二次优化,实现OptInt与Greed2种算法的有效组合。理论分析与仿真实验结果表明,Comb算法具有Greed算法步骤简单、算法复杂度低的优点,在保证消息集可调度前提下,能有效地优化系统的整体性能。 Aiming at real-time messages set with variable period,a mathematical optimization model which expresses the relation between the system performance and the period of messages scheduling by Flexible TimeTriggered(FTT)model is presented.Two algorithms which are called OptInt and Greed respectively are given to find the nearly optimal solution to the period assignment problem.In addition,a new algorithm named as Comb is proposed by combing the two algorithms together,which uses the OptInt algorithm to find the initial solution and improves it with the Greed algorithm.Theoretical analysis and simulation results show that compared with OpInt and Greed algorithms,the Comb algorithm is simple and has lower computation complexity and better optimization effect.
出处 《计算机工程》 CAS CSCD 北大核心 2015年第12期171-175,共5页 Computer Engineering
基金 国家自然科学基金资助项目(61175051 61175033) 国家"973"计划基金资助项目(2013CB329604)
关键词 柔性时间触发 网络控制系统 周期性实时消息 基本周期 周期指定 Flexible Time-Triggered(FTT) network control system periodic real-time message Elementary Cycle(EC) period assignment
  • 相关文献

参考文献12

  • 1Cervin A, Velasco M, Marti P, et al. Optimal Online Sampling Period Assignment: Theory and Experi- ments[ J]. IEEE Transactions on Control Systems Techno-logy, 2011,19 ( 4 ) : 902-910.
  • 2Ben G M,Simon D, Sename O. A Convex Optimization Approach to Feedback Scheduling [ C ]//Proceeings of the 16th Mediterranean Conference on Control and Automation. Washington D. C. , USA : IEEE Press ,2008 : 1100-1105.
  • 3Eker J,Hagander Perztn K E. A Feedback Scheduler for Real-time Controller Tasks [ J ], Control Engineering Practice ,2000,8 ( 12 ) : 1369-1378.
  • 4Ashjaei M, Liu M, Behnam M, et al. Worst-case Delay Analysis of Master-slave Switched Ethernet Net- works[ C]//Proceeings of the 2nd International Work- shop on Worst-case Traversal Time. New Yrok, USA: ACM Press ,2012 : 15-21.
  • 5Marau R, Behnam M, Iqbal Z, et al. Controlling Multi- switch Networks for Prompt Reconfiguration [ C ]// Proceeings of the 9th IEEE International Workshop on Factory Communication Systems. Washington D. C., USA : IEEE Press ,2012:233-242.
  • 6Yekeh F, Pordel M, Almeida L, et al. Exploring Alternatives to Scale FTT-SE to Large Networks [ C ]// Proceeings of the 6th IEEE International Symposium on Industrial Embedded Systems. Washington D. C. , USA: IEEE Press ,2011 : 107-110.
  • 7Yekeh F, Pordel M,Almeida L, et al. Scaling FTT-SE to Large Networks [ C ]//Proceedings of the 6th 1EEE Inter-national Symposium on Industrial Embedded Systems. Washington D. C. , USA: IEEE Press, 2011 : 226-228.
  • 8Ashjaei M, Behnam M, Nolte T, et al. A Compact Approach to Clustered Master-slave Ethernet Net- works[ C]//Proceedings of the 9th IEEE International Workshop on Factory Communication Systems. Washington D. C. , USA : IEEE Press, 2012 : 157-160.
  • 9姚宏亮,张一鸣,李俊照,王浩.动态贝叶斯网络的灵敏性分析研究[J].计算机研究与发展,2014,51(3):536-547. 被引量:11
  • 10方欢,陆阳,徐自军,杨娟.井下机车运输调度的资源分配模型及无死锁优化调度[J].系统工程理论与实践,2013,33(8):2087-2096. 被引量:10

二级参考文献59

  • 1GALL D A. A practical multifactor optimization criterion[M]. New York:Wiley, 1996.
  • 2PARSOPOULOS K, VRAHATIS M. Recent approaches to global optimization problems through particle swarm optimization[J]. Natural Computing, 2002,1 (2-3) : 235- 306.
  • 3LASKARI E, PARSOPOULOS K, VRAHATIS M. Particle swarm optimization for integer programming [C]//Proc of Congress on Evolutionary Computation, Washington DC.. IEEE Computer Society, 2002 : 1582-1587.
  • 4KUSUM D, SRATAP K P,KANSAL M L,et al. A real coded genetic algorithm for solving integer and mixed integer optimization problems [J]. AppliedMathematics and Computation,2009,212:505-518.
  • 5LU Haiyan,CHEN Weiqi. Self-adaptive velocity particle swarm optimization for solving constrained opti- mization problems[J]. Journal Global Optimization, 2007(2) : 138-142.
  • 6DEB K. An efficient constraint handing method for genetic algorithms[J]. Computer Methods in Ap- plied Mechanics and Engineering, 2000, 18(2-4): 311-338.
  • 7LU Haiyan,CHEN Weiqi. Dynamic-objective particle swarm optimization for constrained optimization problems[J]. Combinatorial Optimization, 2006,25 : 409-419.
  • 8DEEP K,SINGH K P,KANSAL M L,et al. A real coded genetic algorithm for solving integer and mixed integer optimization problems[J]. Applied Mathematics and Computation,2009, 212:505-518.
  • 9MOHAN C,NGUYEN H T. A controlled random search technique incorporating the simulating annealing concept for solving integer and mixed integer global optimization problems [J]. Computational Optimization and Applications, 1999,14 : 103-132.
  • 10Nie CH, Leung H. A survey of combinatorial testing. ACM Computing Survey, 2011,43(2):1-29. [doi: 10.1145/1883612.1883618].

共引文献33

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部