Arto Karppanen

Practical power modeling of data transmission over 802.11g for wireless applications

Previous studies have shown that a significant part of the overall energy consumption of battery-powered mobile devices is caused by network data transmission. Power models that describe the power consumption behavior of the network data transmission are therefore an essential tool in estimating the battery lifetime and in minimizing the energy usage of mobile devices. In this paper, we present a simple and practical power model for data transmission over an 802.11g WLAN and show its accuracy against physical data measured from three popular mobile platforms, Maemo, Android and Symbian. Our model estimates the energy usage based on the data transmission flow characteristics which are easily available on all the platforms without modifications to low-level software components or hardware. Based on our measurements and experimentation on real networks we conclude that our model is easy to apply and of adequate accuracy.

Modeling energy efficiency in wireless internet communication

For wireless mobile Internet users the length of the battery life is one of the most important performance factors. The energy efficiency of the data transmission over radio is a key component affecting the battery lifetime. This paper investigates WLAN energy consumption in network communication on a Mobile handset. We introduce an energy model that allows analysis and simulation of the energy efficiency of the Internet protocols on a Wireless Network Interface, and have extended the NS-2 simulation platform to allow investigating the energy consumption of the Radio Modem and the Power Amplifier in WLAN 802.11g network interface of a mobile device. We have also validated our model against measurements on real wireless hardware, and show that the simulation results closely match the real world behavior. We claim to present more detailed and accurate model of the WLAN energy consumption than what is done by the past work that allows designing and optimizing future Internet protocols towards more energy efficient behavior.