Earticle

초록

영어

As to the embedded system of multi-tasks, this paper proposes a hardware/software partitioning algorithm based on Clustering algorithm using reference and density and Genetic algorithm. The algorithm uses reference task to reflect attribute of system task node, and firstly finish classification of task nodes to decrease the scale of the system, and then partitions hardware/software based on genetic algorithm. The experiments results have showed that this algorithm can accelerate converge to appropriate solution of complex system with more tasks.

목차

Abstract
 1. Introduction
 2. Model of Hardware/Software Partitioning
  2.1 Features of model
  2.2 Description of Hardware/Software Partitioning
 3. Partitioning Algorithm of Hardware/software
  3.1 Clustering Algorithm
  3.2 Combination of Clustering Algorithm and Genetic Algorithm
 4. Experiment and Analysis
  4.1 Experimental Samples and Experimental Environment
  4.2 Parameter Setting
  4.3 Experiment Comparison
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Weijia Li [ The College of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China ]
• Lanying Li [ The College of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China ]
• Jianda Sun [ The College of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China ]
• Zhiqiang Lv [ The College of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China ]
• Fei Guan [ The College of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605