The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.

Modeling and Managing Energy Consumption of Mobile Devices

Yu Xiao

Doctoral dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the School of Science for public examination and debate in Auditorium T2 at the Aalto University School of Science (Espoo, Finland) on the 20th of December 2011 at 12 noon.

Overview in PDF format (ISBN 978-952-60-4430-9)   [1047 KB]
Dissertation is also available in print (ISBN 978-952-60-4429-3)


Thanks to the significant improvement in the processing and networking capabilities of mobile devices, mobile devices today can run applications that require complex computation and high network bandwidth. As these applications become ever more popular, a rise is seen in the energy demand that is generated by a typical usage of mobile devices, with the result that existing battery technology is not able to satisfy the growing demand. Improving the energy efficiency of mobile devices and applications has, therefore, become essential. In this thesis, we investigate the energy consumption of mobile devices and propose practical solutions for improving the energy efficiency of wireless data transmission.

We propose power models of wireless data transmission over Wi-Fi and show how the power consumption is related to power-saving mechanisms, to Internet traffic characteristics, and to the network throughput. We utilize the linear dependency of transmission costs on network throughput in order to extend the linear regression power models from microprocessor level to system level. These power models provide us with an insight into developing software with energy-efficient wireless data transmission.

In this thesis, we present three strategies for reducing transmission cost: applying lossless data compression to network traffic data, scheduling the transmission based on the prediction of network conditions, and power management of the wireless network interface based on the predicted traffic intervals. Our strategies consider the trade-offs between computational and transmission costs, and between energy consumption and transmission performance. In addition, we apply statistical methods for implementing prediction utilities. Finally, considering the complexity in the context collection and processing, we propose an event-driven framework that can be used for implementing, deploying and managing various energy-efficient strategies on mobile platforms.

This thesis consists of an overview and of the following 5 publications:

  1. Yu Xiao, Petri Savolainen, Arto Karppanen, Matti Siekkinen, and Antti Ylä-Jääski. Practical Power Modeling of Data Transmission Over 802.11g for Wireless Applications. In Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking, Passau, Germany, 75-84, April 2010.
  2. Yu Xiao, Rijubrata Bhaumik, Zhirong Yang, Matti Siekkinen, Petri Savolainen, and Antti Ylä-Jääski. A System-Level Model for Runtime Power Estimation on Mobile Devices. In Proceedings of 2010 IEEE/ACM International Conference on Green Computing and Communications & 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, Hangzhou, China, 27-34, December 2010. © 2010 Institute of Electrical and Electronics Engineers (IEEE). By permission.
  3. Yu Xiao, Matti Siekkinen, Antti Ylä-Jääski. Framework for Energy-Aware Lossless Compression in Mobile Services: The Case of E-Mail. In Proceedings of 2010 IEEE International Conference on Communications, Cape Town, South Africa, 1-6, May 2010. © 2010 Institute of Electrical and Electronics Engineers (IEEE). By permission.
  4. Ramya Sri Kalyanaraman, Yu Xiao, Antti Ylä-Jääski. Network Prediction for Energy-aware Transmission in Mobile Applications. International Journal on Advances in Telecommunications, issn 1942-2601, Vol.3, no.1&2, 72-82, September 2010. © 2010 by authors.
  5. Yu Xiao, Wei Li, Matti Siekkinen, Petri Savolainen, Antti Ylä-Jääski, Pan Hui. Power Management for Mobile Devices Using Complex Event Processing. Aalto University publication series SCIENCE+TECHNOLOGY Aalto-ST 26/2011, 1-27, 2011. © 2011 by authors.

Keywords: power management, power modeling, mobile devices

This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.

© 2011 Aalto University

Last update 2012-09-27