Earticle

초록

영어

As embedded devices prevail in daily life, high energy consumption caused by embedded software caught academic attentions. Multifarious testing and predicting methods are developed accordingly. This paper proposes a model about energy consumption of embedded device based on analysis of embedded software structure and support vector machine regression. The nonlinear relationship between energy consumption and software structure is revealed. The research finds software structure is determined by features like number of components, complexity of component interface, component coupling, and path length. These features are qualified and modeled by using support vector machine regression and energy consumption is predicted based on this model. The experiments results confirm the proposed model.

목차

Abstract
 1. Introduction
 2. Quantifying with Software Engineering Methods
  2.1. Valid Code Lines Quantifying
  2.2. Number of Components
  2.3. Average Complexity of Components Interface Quantifying
  2.4. Path Length Quantifying
  2.5. Components Coupling Quantifying
 3. Support Vector Machine Regression Prediction
 4. Experimental Results
 5. Conclusion and Future Work
 Acknowledgment
 References

저자

• Xiong Wei [ Computer Science College, Sichuan University, Chengdu, SC 610064, China, Leshan Vocational & Technical College, Leshan, SC 614000, China ]
• Xiaobin Liu [ Computer Science College, Sichuan University, Chengdu, SC 610064, China ]
• Bing Guo [ Computer Science College, Sichuan University, Chengdu, SC 610064, China ]
• Shen Yan [ School of Control Engineering, Chengdu University of Information Technology, Chengdu SC 610225, China ]
• Wenli Zhang [ Computer Science College, Sichuan University, Chengdu, SC 610064, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605