IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering

Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering
View Sample PDF
Author(s): Chris Thompson (Vanderbilt University, USA), Jules White (Vanderbilt University, USA)and Douglas C. Schmidt (Vanderbilt University, USA)
Copyright: 2014
Pages: 26
Source title: Advances and Applications in Model-Driven Engineering
Source Author(s)/Editor(s): Vicente García Díaz (University of Oviedo, Spain), Juan Manuel Cueva Lovelle (University of Oviedo, Spain), B. Cristina Pelayo García-Bustelo (University of Oviedo, Spain)and Oscar Sanjuán Martinez (University of Carlos III, Spain)
DOI: 10.4018/978-1-4666-4494-6.ch016

Purchase

View Analyzing Mobile Application Software Power Consumption via Model-Driven Engineering on the publisher's website for pricing and purchasing information.

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.

Related Content

Babita Srivastava. © 2024. 21 pages.
Sakuntala Rao, Shalini Chandra, Dhrupad Mathur. © 2024. 27 pages.
Satya Sekhar Venkata Gudimetla, Naveen Tirumalaraju. © 2024. 24 pages.
Neeta Baporikar. © 2024. 23 pages.
Shankar Subramanian Subramanian, Amritha Subhayan Krishnan, Arumugam Seetharaman. © 2024. 35 pages.
Charu Banga, Farhan Ujager. © 2024. 24 pages.
Munir Ahmad. © 2024. 27 pages.
Body Bottom