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Power management of a computer display
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The goal with this project is to investigate how the energy management

can be improved on a linux computer. Focus lies on the screen back light

as this is one of the major energy consumers in a laptop computer. In the

systems available today the regulation is static and the back light is set

in fixed steps without the user behavior in consideration. Adaboost is a

machine learning algorithm that is implemented in a software daemon

to regulate the back light adaptive. The algorithm is trained with data

containing the user demands in the specific system state. Data covering

key presses per time, actual brightness,battery level and the information

if power cord is plugged in or not. The algorithm will continuously classify

the current system state and increase or decrease the back light. A

statistical study shows that the daemon consumes more energy than the

original system. Future developments and improvements are discussed.

Abstract [sv]

Detta projekt syftar till att undersöka hur energihanteringen kan förbättras

på en Linuxdator. Fokus i implementationen ligger på skärmens

bakgrundsbelysning eftersom detta är en av de största energiförbrukarna

i en bärbar dator. I de system som finns tillgängliga idag så sker

regleringen statiskt och bakgrundsbelysningen regleras i fasta steg utan

anpassning till användarens beteende. Adaboost som är en lärande algoritm

implementeras i en mjukvaru daemon för att reglera ljusstyrkan

adaptivt. Algoritmen tränas med data för användarens önskemål i det

aktuella körläget med avseende på tangenttryckningar per tid, aktuell

ljusstyrka, batterinivå och information om strömkabeln är inkopplad eller

ej. Algoritmen klassificerar sedan kontinuerligt aktuellt körläge och

höjer eller sänker bakgrundsbelysningen adaptivt. En statistisk undersökning

visar att vår energihanterare drar mer ström än om den är

inaktiv. Framtida utveckling och förbättringar diskuteras

Place, publisher, year, edition, pages
2013.
Series
Kandidatexjobb CSC, K13022
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-134912OAI: oai:DiVA.org:kth-134912DiVA: diva2:668716
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2013-12-13 Created: 2013-12-02 Last updated: 2013-12-13Bibliographically approved

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Power management of a computer display(381 kB)35 downloads
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