文章基本信息

标题：An Embedded Software Power Consumption Model based on Software Architecture and Support Vector Machine Regression
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作者：Xiong Wei ; Xiaobin Liu ; Bing Guo 等
期刊名称：International Journal of Smart Home
印刷版ISSN：1975-4094
出版年度：2016
卷号：10
期号：3
页码：191-200
DOI：10.14257/ijsh.2016.10.3.19
出版社：SERSC
摘要：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.