TOWARDS ENERGY-EFFICIENT DATA TRANSMISSION ON MOBILE DEVICES

PhD Thesis Proposal Defence


Title: "TOWARDS ENERGY-EFFICIENT DATA TRANSMISSION ON MOBILE DEVICES"

by

Mr. Yi ZHANG


Abstract:

The evolving mobile network, which provides fast and flexible access to the 
Internet, has greatly changed our daily life. Various Apps and services are now 
supported on mobile devices and thus, facilitates our research, work and so on. 
However, constrained to the current technologies, the energy-inefficient mobile 
data transmission often hinders people from fully enjoying current mobile 
network. In order to address this issue, in this thesis, we aim to solve some 
tightly-related challenges to achieve energy-efficient mobile data transmission 
and thus, narrow down the gap between our daily life and fast evolving mobile 
technologies.

First, we study the energy issues of uncontrolled App network activities in 
mobile phones. As more and more applications being installed, their competition 
for network resources incurs serious problems to battery life and thus, degrade 
users' normal experiences. To address this issue, we make comprehensive 
measurements on users habit and propose a novel approach to orchestrate network 
activities of smartphone applications, based on users habit. The proposed 
algorithm is proven to approximates the online optimal solution with a 
competitive ratio of (1-epsilon)/2 . We implement the algorithm as a middleware 
service and it achieves over 70% energy savings in network activities.

Then we move our focus onto a more essential factor, the variation of WiFi link 
quality. Nowadays, o ffloading mobile traffic from cellular to WiFi is widely 
recognized as a viable solution to improve the energy efficiency on mobile 
devices. However, through extensive field experiments, we find WiFi offloading 
is not always energy efficient and even consumes more energy than cellular 
network due to link quality variation. On the other hand, we observe from our 
past experiences that practical data transmission deadline requirement and link 
utilization allows scheduling of data traffic to time periods with good link 
quality. Accordingly, we propose Q-offload, the first attempt towards energy 
efficient WiFi o ffloading with link dynamics. In Q-offload, we propose an 
iterative framework to achieve energy efficient WiFi o ffloading by exploiting 
good link quality while not affecting user experience. The results from 
extensive experiments show that Q-offl oad can achieve 33.5%~55.7% energy 
efficiency improvement, compared with state-of-the-arts under different 
conditions.

Enlightened by the results of our prior works, we raise our focus onto users' 
lifestyles and this constitutes our third work. In this work, we propose a 
context-based link quality estimation scheme for achieving energy-efficient 
data transmission in WiFi/mobile networks. Through analyzing millions of user 
traces, we exploit that link quality is highly relevant with users' lifestyle 
and can be extracted as fingerprints. Following this observation, we propose a 
individual-oriented system, Furion, for exploiting beneficial WiFi/mobile links 
based on users' contexts. In Furion, we introduce a context-based link quality 
discrimination scheme and design a more practical probabilistic model to 
predict the energy efficiency of links. As a result, the accuracy of link 
quality estimation is further improved given limited hardware on mobile devices 
and it can also be extended to different environments. The prototype of Furion 
is implemented on Android platform and the results demonstrate that Furion 
achieves a significant performance improve compared with the state-of-the-arts.


Date:			Tuesday, 10 January 2017

Time:                  	2:00pm - 4:00pm

Venue:                  Room 4472
                         (lifts 25/26)

Committee Members:	Prof. Bo Li (Supervisor)
  			Prof. Lei Chen (Supervisor)
 			Dr. Kai Chen (Chairperson)
  			Dr. Ke Yi


**** ALL are Welcome ****