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Permanent link (DOI): https://doi.org/10.7939/R3251FT35

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Using System Calls to Predict Changes in Application Energy Consumption Profiles Open Access

Descriptions

Other title
Subject/Keyword
System calls
Energy efficient software
Software energy consumption
Green mining
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Aggarwal, Karan
Supervisor and department
Hindle, Abram (Computer Science)
Stroulia, Eleni (Computing Science)
Examining committee member and department
Stroulia, Eleni (Computing Science)
Hindle, Abram (Computer Science)
Wong, Kenny (Computing Science)
Hoover, H. James (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2015-08-18T09:19:38Z
Graduation date
2015-11
Degree
Master of Science
Degree level
Master's
Abstract
Battery is a limiting resource that affects the smartphone availability. Hence, it is the responsibility of developers to develop and maintain energy efficient applications to enhance end user satisfaction. As the impact of software code change on energy consumption is not known, developers need special instrumentation to assess the impact of change on their application’s energy consumption profile. Unfortunately, this instrumentation is costly and generally not available. In order to address this issue, we use system calls to predict the impact of code changes on the energy consumption profile. We find that significant changes to system call profiles often induce significant changes in energy consumption. Using this simple observation, we introduce GreenAdvisor, a first of its kind tool that systematically records and analyzes an application’s system-calls in order to predict whether the energy-consumption profile of an application has changed. The GreenAdvisor tool was evaluated using a user study whereby numerous software teams, whose members used GreenAdvisor while developing Android applications to examine the energy-consumption impact of selected commits from the teams’ projects. The evaluation confirms the usefulness of our tool in assisting developers analyze and understand the energy-consumption profile changes of a new version. This work is useful for the developers who are grappling with paucity of tools or knowledge to find out impact of changes on their application’s energy consumption.
Language
English
DOI
doi:10.7939/R3251FT35
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Karan Aggarwal, Chenlei Zhang, Joshua Charles Campbell, Abram Hin- dle, and Eleni Stroulia. The power of system call traces: Predicting the software energy consumption impact of changes. In Press of the 2014 Conference of the Center for Advanced Studies on Collaborative Research, IBM Corp, 2014.  http://dl.acm.org/citation.cfm?id=2735546Karan
Aggarwal, Abram Hindle, and Eleni Stroulia. GreenAdvisor: A Tool for Analyzing the Impact of Software Evolution on Energy Consump- tion. In International Conference on Software Maintenance and Evolution (ICSME). to be published, 2015.

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