Yong Wang 35 Olden Street Princeton, NJ 08540 USA (609) 258-2072 yongwang@princeton.edu http://www.cs.princeton.edu/˜yongwang OBJECTIVE Seeking a full-time research or R&D position (2007) in the areas of networks, systems and performance evaluation. EDUCATION Princeton University, Princeton, NJ USA Graduate Student, Computer Science (since Sept, 2001) Advisors: Margaret Martonosi, Li-Shiuan Peh Peking University, Beijing, China M.S., Computer Science (1998 - 2001) Advisor: Xiaoming Li Beijing Institute of Technology (BIT), Beijing, China B.E., Computer Science and Engineering (1994 - 1998) ACADEMIC AND RESEARCH EXPERIENCE Thomson Research, Princeton, NJ USA Summer Intern June, 2006 - August, 2006 Worked on high accuracy localization systems using sensor networks (the MIT cricket system) for media production applications. I built a system prototype using the MIT/XBow Cricket system and conducted accuracy evaluation in a studio-like environment. An improvement over Cricket is proposed and implemented. Intel Research, Hillsboro, OR USA Summer Intern June, 2005 - Sept, 2005 Worked on reliable delivery in intermittently-connected sensor networks. As a first step, I implemented a tool-set for sensor data/configuration file transport that supports disconnection tolerant operations on the cluster head level in a hierarchal sensor network. Also worked on mesh routing in a network of Stargate nodes. Manager: Mark Yarvis Princeton University, Princeton, NJ USA Graduate Student September, 2001 - present I have been part of the broader ZebraNet project, a mobile, wireless sensor network where nodes move throughout an environment working to gather and process information about their surroundings. More recently, I am working on energy-efficient, situation-aware optimizations in routing and data collection for various emerging challenged networks. In the meanwhile, I have gained experience and proficiency for both ns-2 and TinyOS/nesC programming and development. [aDapTN] This work aims to improve idle energy efficiency in challenged networks such as intermittently-connected sensor networks. We propose a staged data transport based on DTN techniques to accommodate the unique characteristics of communications in such environments. [MetricMap and SHARP] The goal of this work is to enable situation-awareness in sensor network routing using machine learning and data mining techniques. As a case study, we propose to apply supervised learning to link quality estimation in wireless sensor networks. Our-learning based approach can find good links in a range of traffic patterns and outperform the state-of-the-art protocols. This approach potentially makes better predictions about system and network conditions and can enable more accurate and fine-grained routing decisions. [Transformer] This project proposes a model-driven mobility-aware scheme where protocols can be re-configured in the presence of varying mobility. We study analytical models to capture the interaction between node mobility and protocol behavior. We then use the model to detect abnormal routing performance in terms of route cache staleness and to drive adaptive decisions on-the-fly. This approach outperforms a simulation-based approach in terms of speed. Several results are under submission right now. [Erasure-coding based routing in opportunistic networks] This work proposes a novel usage of erasure codes to cope with mobility challenges in opportunistic networks where contacts are rare and hard to predict. [MARio] As mobility is very unpredictable in nature, it is well accepted that there is no single protocol that works for all scenarios. How to design adaptive protocols to automatically matching the environments is very challenging. We propose MARio, a mobility-adaptive framework for driving adaptive decisions by leveraging knowledge exposed from mobility statistics. Rather than setting up protocol parameters manually based on heuristics or a trial-and-error process, we choose to guide routing decisions based on mobility knowledge learned from past observation. In particular, we abstract node mobility using route lifetime as a case study. This results in a self-adaptive protocol that applies to varying mobility in a resource-efficient way. Teaching Assistant Feb, 2004 - May, 2004 COS333 Advanced Programming Techniques, by Prof. Brian Kernighan, Princeton University. Teaching Assistant Sept, 2002 - Jan, 2003 COS318 Operating System, by Prof. Vivek Pai, Princeton University. Peking University, Beijing, China SOFTWARE DEVELOPMENT -Proficient in C/Python. Working knowledge of Java/Perl. -Proficient in socket-based network programming, web programming and GNU software tools and environment. -Proficient in data processing and analysis using various script languages, such as awk, Python, and Perl. Implemented a tool-set for automatically processing traces from MoteLab and mobility traces from the ZebraNet deployment in Africa. -Author of SFB, a tool-set written in Perl to support disconnection tolerant operations in an intermittently-connected sensor network. -Co-author of ZnetSim, a C-based simulator for ZebraNet project. Designed and implemented the peer-to-peer, store-and-forward based routing protocols. -Extensive experience with ns-2 and TinyOS/NesC development, including building system prototype using TinyOS/NesC, extending ns-2 wireless ad-hoc routing network stack and implementing routing applications. -Familiar with WEKA, a machine learning toolset implemented in JAVA. -Familiar with Matlab. PUBLICATIONS Yong Wang, Margaret Martonosi, and Li-Shiuan Peh, Supervised Learning in Sensor Networks: New Approaches with Routing, Reliability Optimizations, in Proceedings of IEEE Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON 2006), Reston, VA, September, 2006 Yong Wang, Chieh-Yih Wan, Margaret Martonosi, and Li-Shiuan Peh, Transport Layer Approaches to Improve Idle Energy in Challenged Sensor Networks, in Proceedings of ACM SIGCOMM Workshop on Challenged Networks (CHANTS 2006), Pisa, Italy, September, 2006 Yong Wang, Margaret Martonosi, and Li-Shiuan Peh, Situation-Aware Caching Strategies in Highly Varying Mobile Networks, in Proceedings of IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2006), Monterey, CA, September, 2006 Yong Wang, Margaret Martonosi, and Li-Shiuan Peh, A Supervised Learning Approach for Routing Optimizations in Wireless Sensor Networks, in Proceedings of ACM/SIGMOBILE Workshop on Multi-hop Ad Hoc Networks: from theory to reality (REALMAN 2006), Florence, Italy, May, 2006 (in conjunction with ACM MobiHoc 2006) Yong Wang, Margaret Martonosi, and Li-Shiuan Peh, Poster Abstract: A New Scheme on Link Quality Prediction and its Applications to Metric-Based Routing, in Proceedings of ACM SenSys, 2005 Yong Wang, Sushant Jain, Margaret Martonosi, and Kevin Fall, Erasure Coding Based Routing for Opportunistic Networks, in Proceedings of ACM SIGCOMM Workshop on Delay Tolerant Networking and related topics (WDTN-05), 2005. Yong Wang, Margaret Martonosi,and Li-Shiuan Peh, MARio: Mobility-Adaptive Routing Using Route Lifetime Abstractions in Mobile Ad Hoc Networks, ACM SIGMOBILE Mobile Communication and Communications Review (MC2R), Volume 8, Issue 4 (October 2004). Yong Wang, Margaret Martonosi, and Li-Shiuan Peh, MARio: Mobility-Adaptive Routing Using Route Lifetime Abstractions in Mobile Ad Hoc Networks, Poster Presentation in ACM MobiHoc, 2004. Philo Juang, Hide Oki, Yong Wang, Margaret Martonosi, Li-Shiuan Peh, and Daniel Rubenstein, Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet, In Proceedings of ASPLOS-X, 2002. PROFESSIONAL EXPERIENCE Reviewer for ACM SenSys, NSDI, IEEE Transactions on Mobile Computing, ACM Computer Communication Review (CCR), IEEE ICDCS, DCOSS, IEEE ICC and WCNC HONORS AND AWARDS -Princeton Graduate School Dean's Travel Funds, 2006 -SECON'06 Student Travel Grant, 2006 -SenSys'05 Student Travel Grant, 2005 -Princeton Graduate Fellowship, Princeton University, 2001-2002 -Guang-Hua Fellowship, Peking University, 1999-2000 -Samsung Fellowship, among universities in China, SAMSUNG Inc., 1997-1998 -Best undergraduate thesis award, BIT, 1998 -First Prize Winner of English Essay Writing, Beijing, 1997 -Second Prize Winner of Collegiate Student Programming Contest, BIT, 1996 COMPUTER SKILLS Languages and Tools: C, Java, Python, Perl, ML, awk, Unix shell, Latex, MPI, OpenMP, Matlab. Operating Systems: Unix/Linux, Windows, MacOS. REFERENCES: Margaret Martonosi Professor Department of Electrical Engineering B216 Engineering Quad Princeton University Princeton, NJ 08544 +1 609 258 1912 mrm@princeton.edu Li-Shiuan Peh Assistant Professor Department of Electrical Engineering B228 Engineering Quad Princeton University Princeton, NJ 08544 +1 609 258 7747 peh@princeton.edu