I am a researcher (Senior Member of Technical Staff)
in Mobile and Pervasive Systems Research group at AT&T Labs Research.
I am broadly interested in solving challenging problems
related to cloud and mobile systems.
I earned a Ph.D. degree in the Computer Science Department at
University of Southern California (USC) in 2013.
Currently I am looking for an intern student in the area of software-defined storage.
Please drop me an email if you are interested in spending this summer in AT&T Labs-Research.
Current Research Interest (but not limited to..)
Guaranteeing SLAs on Storage Traffic in Data Centers
Wide-area Resource Optimization in Multi-Data Centers
Privacy-Preserving Imaging Systems and Applications for Mobile Devices
Cloud-Enabled Mobile Systems and Applications
- Moo-Ryong Ra, Ramesh Govindan, and Antonio Ortega
Moo-Ryong Ra, Bodhi Priyantha, Aman Kansal, and Jie Liu
- "Improving Energy Efficiency of Personal Sensing Applications with Heterogeneous Multi-Processors",
- ACM Ubicomp 2012, [paper]
- Moo-Ryong Ra, Bin Liu, Tom La Porta, and Ramesh Govindan
- Moo-Ryong Ra, Anmol Sheth, Lily M. Mummert, Padmanabhan Pillai, David Wetherall, and Ramesh Govindan
- Moo-Ryong Ra, Jeongyeup Paek, Abhishek B. Sharma, Ramesh Govindan, Martin H. Krieger, and Michael J. Neely
Past Research Projects
Privacy-Preserving Photo Sharing
Photo sharing services, e.g. Facebook and Flickr, are getting more popular nowadays, however, there are no protection of users' photos against the photo sharing service providers (PSPs). We are just forced to trust PSPs. In this work, we develop a photo encryption algorithm that can preserve privacy against PSPs while still maintaining the useful processing services provided by them, e.g. image scalability and quality enhancement. We also built a prototype transparently worked with Facebook. (prototype, NSDI'13)
Programming Crowd-Sensing Task
Design and implementation of a high level programming language and associated runtime for crowd-sensing applications. The framework makes two strands of topics extremely easy to program, a) tasking smartphones and b) dealing with human mediation and incentives. (code, demo video, MobiSys'12)
Attempt to answer the following question: In order to enable continuous personal sensing applications on mobile devices, how should we use ultra low power processor(LP) with an existing application processor(AP)? Investigate representative app components and explore the placement strategy between AP and LP that brings minimum energy consumption. (with MSR Redmond SERG group, Ubicomp'12)
Enabling Perception Applications on Mobile Devices
Partitioning mobile perception applications across mobile devices and the cloud infrastructure focusing on the performance. Design and implementation of lightweight, i.e. sub-second decision granularity, dynamic decision engine and associated runtime that can adapt to input variability, network and device heterogeneity in real-time. (with Intel Labs Seattle, MobiSys'11)
Energy-Efficient Network Interface Selection
Design and implementation of SALSA (Stable and Adaptive Link Selection Algorithm) for high data-rate and delay-tolerant mobile applications. Our algorithm intelligently defers the transmission opportunity to the future based on Lyapunov optimization framework anticipating that more energy-efficient WiFi AP, rather than 3G, would be avaiable soon. (MobiSys'10)
Automatic Video Uploading System
We built an Urban Tomography system, which collects high resolution videos using smartphones and automatically uploads them to an Internet-connected server without any user interventiton. When transfer, the system deals with an automatic AP management issue, e.g. chunking data, network profiling for proper AP selection, blacklisting, etc. It had deployed to the LAX international airport for more than a year and the course projects in USC and UCLA. (JUT'10, JPER'09, [poster])
|Initially created: 8th Oct. 2007 , Last Modified: 26th Feb. 2014|