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Author: | Chowdhury, Mohammad Khaled Hasan |
Title: | Traffic-aware adaptive network interface control for energy-efficiency in wireless data transmission |
Publication type: | Master's thesis |
Publication year: | 2010 |
Pages: | [9] + 68 Language: eng |
Department/School: | Informaatio- ja luonnontieteiden tiedekunta |
Main subject: | Tietokoneverkot (T-110) |
Supervisor: | Ylä-Jääski, Antti |
Instructor: | Xiao, Yu |
OEVS: | Electronic archive copy is available via Aalto Thesis Database.
Instructions Reading digital theses in the closed network of the Aalto University Harald Herlin Learning CentreIn the closed network of Learning Centre you can read digital and digitized theses not available in the open network. The Learning Centre contact details and opening hours: https://learningcentre.aalto.fi/en/harald-herlin-learning-centre/ You can read theses on the Learning Centre customer computers, which are available on all floors.
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Location: | P1 Ark Aalto | Archive |
Keywords: | wireless network interface adaptive traffic energy efficient prediction |
Abstract (eng): | The Wireless Network Interface (WNI) are widely deployed on modern mobile devices, which makes it possible to access internet services such a audio and video streaming from mobile devices. Due to the intensive computation and network transmission caused by the internet services, power consumption has become big challenge to the mobile devices powered by batteries. The network transmission cost is mainly caused by the operations of the VNI, such as Receiving/transmitting data or staying in the idle mode. In this thesis we present an adaptive control algorithm of a wireless network interface (WNI) for energy efficiency. Our algorithm aims at controlling the operating modes of the WNI in such a way that the WNI can go to sleep mode instead of staying in idle mode when it is predicted to be no traffic for a certain period. The adaptation takes the overhead of the transition between IDLE and SLEEP modes into account, and the adaptation is combined with an ARIMA-based, prediction algorithm of the traffic patterns. We evaluate our algorithm with the power measurement from Nokia N810, and the experimental results show that our adaptation can save up to 20% energy than standard PSM during WLAN data transmission in streaming applications such as LiveTV and YouTube. |
ED: | 2010-10-13 |
INSSI record number: 41070
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