ECE seminar series: The Case for Transmit Only Communication

Wednesday, April 10, 2013 ( 3:00 pm to 4:00 pm )

Location: Babbio Center, Room 319

Prof. Yingying Chen ([email protected])


The Case for Transmit Only Communication

BY Dr. Richard P. Martin

Associate professor

Computer Science Department, Rutgers University



The past 15 years has seen significant investigation of sensing networks, however, widespread adoption has yet to occur. In this talk, we describe a new class of Transmit Only (TO) protocols that addresses this gap. The key observation is that we can greatly improve the simplicity, reliability and energy consumption of the sensors by using a small network of well-connected, powered receivers. Comparing several generations of sensor nodes to a TO design, we first show that the TO approach reduces the sensors’ size, cost and energy needs by several factors. Using analytic models, we demonstrate that TO protocols’ energy consumption per delivered bit can exceed carrier sensing and time division approaches by aggressive exploitation of the capture effect, which we effect by using message-in-messaging and strategic receiver placement.  Our measurements show that a real 500 sensor network running a TO protocol can last 3 years with a coin cell battery per node, using only 3 receivers.



Dr. Richard P. Martin is an associate professor of computer science at Rutgers University and a member of the Rutgers Wireless Network Information Laboratory (WINLAB). His current research interests include parallel computing, wireless device localization, and human factors in dependable computing. His awards include the best paper award at the IEEE Conference on Sensor and Ad Hoc Communication Networks and the ACM conference on Mobile Computing and Networking, as well as a CAREER award from the National Science Foundation. Dr. Martin has served as an investigator on grants from the Defense Advanced Research Projects Agency, the National Science Foundation, and IBM. He received a B.A. from Rutgers University and an, M.S. and Ph.D. in computer science the University of California at Berkeley.