Optimising Energy Consumption Heuristically on Android Mobile Phones

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InProceedings{Bokhari:2016:GI,

• author = "Mahmoud Bokhari and Markus Wagner",
• title = "Optimising Energy Consumption Heuristically on {Android} Mobile Phones",
• booktitle = "Genetic Improvement 2016 Workshop",
• year = "2016",
• editor = "Justyna Petke and David R. White and Westley Weimer",
• pages = "1139--1140",
• address = "Denver",
• publisher_address = "New York, NY, USA",
• month = jul # " 20-24",
• organisation = "SIGEvo",
• publisher = "ACM",
• keywords = "genetic algorithms, genetic programming, Genetic Improvement, SBSE, Embedded systems, Computing methodologies, Heuristic function construction, Randomized search, Power Consumption Modelling, Energy Optimisation",
• URL = "http://cs.adelaide.edu.au/~markus/pub/2016-gecco-gi-energy.pdf",
• URL = "http://geneticimprovementofsoftware.com/wp-content/uploads/2016/06/Optimising_Energy_Consumption_Heuristically_on_Android_Mobile_Phones.pdf",
• DOI = "doi:10.1145/2908961.2931691",
• size = "2 pages",
• abstract = "In this paper we outline our proposed framework for optimising energy consumption on Android mobile phones. To model the power usage, we use an event-based modelling technique. The internal battery fuel gauge chip is used to measure the amount of energy being consumed and accordingly the model is built on. We use the model to estimate components' energy usages. In addition, we propose the use of evolutionary computations to prolong the battery life. This can be achieved by using the power consumption model as a fitness function, re-configuring the smartphone's default settings and modifying existing code of applications.",
• notes = "GECCO-2016 Workshop http://geneticimprovementofsoftware.com/",

}

Genetic Programming entries for Mahmoud A Bokhari Markus Wagner

Citations