Predicting mobile application power consumption

dc.contributor.advisor	Green, Mark
dc.contributor.author	Chang, Michael
dc.date.accessioned	2018-07-24T14:23:12Z
dc.date.accessioned	2022-03-29T17:25:50Z
dc.date.available	2018-07-24T14:23:12Z
dc.date.available	2022-03-29T17:25:50Z
dc.date.issued	2018-05-01
dc.identifier.uri	https://hdl.handle.net/10155/934
dc.description.abstract	We present an analysis of battery consumption to predict the average consumption rate of any given application. We explain the process and techniques used to gather the data, and present over 25000 readings collected over 3 months. We then use iterative proportional fitting to predict the consumptions rates, discuss the issues with the collected data, and highlight the attempts made to alleviate the problems. Lastly, we discuss the limitations and challenges of this approach, and suggest changes that may be required in order to produce more accurate results.	en
dc.description.sponsorship	University of Ontario Institute of Technology	en
dc.language.iso	en	en
dc.subject	Prediction	en
dc.subject	Mobile	en
dc.subject	Power	en
dc.subject	Smartphone	en
dc.title	Predicting mobile application power consumption	en
dc.type	Thesis	en
dc.degree.level	Master of Science (MSc)	en
dc.degree.discipline	Computer Science	en