Tong Jin
Email: tongjin@winlab.rutgers.edu
This web site will NOT be maintained, please visit:
https://www.eden.rutgers.edu/~tjin/index.html
About me
Currently, I am pursuing my Ph.D degree at Rutgers University.
I received my MS Degree at Winlab (Wireless Information & Networking Laboratory), Rutgers University in May 2011, under the guidance of Prof.Marco Gruteser.
Before coming to Rutgers, I received my B.E. Degree in 2008, from Nanjing University of Posts & Telecommunications, Nanjing, P.R China.
My research interests are broadly in distributed systems, parallel computing, mobile systems, vehicular networks, wireless sensor networks, and ITS. In 2010, my work on mobile sensing was featured in the MIT Technology Review and won the Best Paper Award in 2010 Mobisys conference.
My work in the press: MIT Technical Review | CBC News | Popular Science | Discover Magazine | ACM Tech News
Resume |
Research Experience
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WIMAX based Vehicular Network Demonstration for 9th GENI & NSF conference( Feb 2010~Jan 2011 )Orbit Testbed is a two-tier laboratory emulator/field trial network testbed designed to achieve reproducibility of experimentation, while also supporting evaluation of protocols and applications in real-world settings. We implement a delay-tolerant vehicular system on ORBIT Testbed through WiMAX connection, which continually collects data and shows the real time data visualization results. Several onboard client nodes with WiMAX driver are distributed in this network. By utilizing Orbit Measurement Framework and designed delay-tolerant mechanism, different network performance measurements and various application data are collected and centralized to the remote server through WiMAX, and then visualized at real-time. |
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ParkNet (Mobile Sensing Network)( May 2009~June 2010 )Real-time information on the availability of street-parking spaces in urban areas is likely to greatly lower traffic congestion, but is difficult to obtain without incurring huge costs. ParkNet is a experimental vehicular sensor network deployed on vehicles belonging to volunteering graduate students. The system uses sensor data to opportunistically gather and disseminate information about available street parking spaces using a city-wide mobile sensing network (say, using taxicabs as sensor vehicles). ParkNet vehicles employ a simlpe GPS receiver and a low cost ultrasonic rangefinder to accurately detect parked cars. The data is aggregated at a central server, which builds a real-time map of the city's parking availability. The cost/benefit ratio of the system scales much better than a stationary sensor network and can be immensely useful to mobile users looking for parking, city planners, and parking enforcement authorities. |
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