Tingjun Chen and Professors Ghaderi and Zussman Received the ACM CoNEXT'16 Best Paper Award

Ph.D. student Tingjun Chen and Professors Javad Ghaderi, Dan Rubenstein (CS), and Gil Zussman will receive the Best Paper Award at ACM CoNEXT’16:

T. Chen, J. Ghaderi, D. Rubenstein, and G. Zussman, “Maximizing broadcast throughput under ultra-low-power constraints,” in Proc. ACM CoNEXT’16, Dec. 2016.

ACM CoNEXT (the 12th International Conference on emerging Networking EXperiments and Technologies) is a premier, single track networking conference focusing on innovative developments on networking technologies. This year, the conference received 196 submissions and the acceptance ratio was 18.4%.

The paper was motivated by wireless object tracking and Internet of Things (IoT) applications such as the ones envisioned in the EnHANTs project. Such applications will soon utilize emerging ultra-low-power device-to-device communication. However, severe energy constraints require much more careful accounting of energy usage than what prior art provides. Therefore, the paper formulates the problem of maximizing the throughput among a set of heterogeneous broadcasting nodes with differing power consumption levels, each subject to a strict ultra-low-power budget. Lagrangian methods are used to design EconCast – a simple asynchronous distributed Energy-constrained Broadcast protocol which aims to maximize the throughput given these budgets. The performance of EconCast is evaluated numerically and via extensive simulations and it is shown that EconCast outperforms prior art by 6x – 17x under realistic assumptions. Moreover, EconCast is implemented using the Commercial Off-The-Shelf (COTS) energy harvesting nodes to demonstrate its practicality.

The student author, Tingjun Chen, is currently a Ph.D. student in the WiMNet Lab. He received his B.Eng. degree in Electronic Engineering from Tsinghua University, Beijing, China, in 2014. He joined Columbia EE as an M.S./Ph.D student in Fall 2014 and received the M.S. degree in Oct. 2015. His research interests are in the areas of algorithms, optimization, MAC layer design, and system implementation for wireless networks, energy harvesting networks, and full-duplex networks. He received the Wei Family Private Foundation Fellowship (2014 – 2017) and the Columbia University Electrical Engineering Armstrong Memorial Award.


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