Mobile devices are being transformed into a ubiquitous computing platform, resulting in profound impact on the way we live, work and play. New mobile applications with advanced features are being created every day and finding their way into our lives. However, this trend toward omnipotent mobile Internet is hampered by the fact that mobile devices, compared to their desktop counterparts, are inherently resource-poor, due to limited computing power and battery lifetime. As a result, there exists a tussle between computation-intensive applications and resource-poor mobile devices. Recently, a mobile cloud computing paradigm is emerging and is capable of answering the needs of computation-intensive mobile applications, and reflects the principal investigator's vision of carry small enjoy large: carry a small mobile device while enjoying a large amount of resources offered by cloud computing infrastructure. Under this paradigm, a small mobile device can deliver a rich experience of computing, telephony, multimedia, entertainment, gaming, and Internet.

To realize the vision of carry small enjoy large, this project is intended to develop new theories and techniques with the promise of significantly advancing the current technologies of mobile cloud computing. To accomplish this, the following research tasks will be conducted: 1) developing a computing-task scheduling approach based on Markov decision process and effective capacity, which is capable of achieving optimal energy consumption while guaranteeing user-specified task-completion delay performance over fading channels; 2) designing a data-prefetch scheduler for mobile video streaming, which minimizes the cost incurred by unconsumed video data while satisfying the viewer's quality of experience; 3) designing a resource-optimized video codec that guarantees low delay and high quality of experience for gaming video; and 4) developing a real-time wireless testbed.

The proposed approaches will fill some important gaps in fundamental understanding of mobile cloud computing and networking over time-varying fading channels, and will provide the theoretical underpinning for system design and algorithm implementation. The proposed approach to computing-task scheduling will not only provide an enabling technology that realizes our vision of carry small enjoy large, but also push the frontier of green computing technologies. The project will involve graduate and undergraduate students, and attract students from underrepresented groups. The mobile cloud computing applications will offer an ideal platform to engage undergraduate and K-12 students with enhanced education and research experience.

The transformative aspect of the project is that the proposed research on mobile cloud computing will result in new methodologies for the design of mobile video streaming systems and cloud gaming systems with unprecedented capabilities of achieving optimal resource usage and high quality of experience.

Project Start
Project End
Budget Start
2015-08-01
Budget End
2019-07-31
Support Year
Fiscal Year
2015
Total Cost
$308,000
Indirect Cost
Name
University of Florida
Department
Type
DUNS #
City
Gainesville
State
FL
Country
United States
Zip Code
32611