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Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering

Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering

Chris Thompson, Jules White, Douglas C. Schmidt
Copyright: © 2014 |Pages: 26
ISBN13: 9781466644946|ISBN10: 146664494X|EISBN13: 9781466644953
DOI: 10.4018/978-1-4666-4494-6.ch016
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MLA

Thompson, Chris, et al. "Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering." Advances and Applications in Model-Driven Engineering, edited by Vicente García Díaz, et al., IGI Global, 2014, pp. 342-367. https://doi.org/10.4018/978-1-4666-4494-6.ch016

APA

Thompson, C., White, J., & Schmidt, D. C. (2014). Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering. In V. Díaz, J. Lovelle, B. García-Bustelo, & O. Martinez (Eds.), Advances and Applications in Model-Driven Engineering (pp. 342-367). IGI Global. https://doi.org/10.4018/978-1-4666-4494-6.ch016

Chicago

Thompson, Chris, Jules White, and Douglas C. Schmidt. "Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering." In Advances and Applications in Model-Driven Engineering, edited by Vicente García Díaz, et al., 342-367. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-4494-6.ch016

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Abstract

Smartphones are mobile devices that travel with their owners and provide increasingly powerful services. The software implementing these services must conserve battery power since smartphones may operate for days without being recharged. It is hard, however, to design smartphone software that minimizes power consumption. For example, multiple layers of abstractions and middleware sit between an application and the hardware, which make it hard to predict the power consumption of a potential application design accurately. Application developers must therefore wait until after implementation (when changes are more expensive) to determine the power consumption characteristics of a design. This chapter provides three contributions to the study of applying model-driven engineering to analyze power consumption early in the lifecycle of smartphone applications. First, it presents a model-driven methodology for accurately emulating the power consumption of smartphone application architectures. Second, it describes the System Power Optimization Tool (SPOT), which is a model-driven tool that automates power consumption emulation code generation and simplifies analysis. Third, it empirically demonstrates how SPOT can estimate power consumption to within ~3-4% of actual power consumption for representative smartphone applications.

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