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Home | Seminars and Symposia | Past seminars/symposia: Tuesday, October 20, 2009

DTC Seminar Series

A multi-objective optimization approach for sensor network design


Ramesh Rajagopalan
St. Thomas

Tuesday, October 20, 2009
4:00 pm

402 Walter Library

Many sensor network design problems are characterized by the need to optimize multiple conflicting objectives. However, existing approaches generally focus on a single objective (ignoring the others), or combine multiple objectives into a single function to be optimized, to facilitate the application of classical optimization algorithms. This restricts their ability and constrains their usefulness to the network designer. A much more appropriate and natural approach is to address multiple objectives simultaneously, applying recently developed multi-objective evolutionary algorithms for solving sensor network design problems. This talk describes and illustrates this approach by modeling the sensor placement problem for plume detection as a multi-objective optimization problem, developing the appropriate objective functions, and discussing the tradeoffs between them.


Ramesh Rajagopalan received the Master’s (Honors) degree in Physics and the B.E (Honors) degree in Electrical and Electronics from the Birla Institute of Technology and Science, Pilani, India in 2002. He received a PhD (Electrical Engineering) from Syracuse University, Syracuse, NY in 2008. He was a Visiting Assistant Professor at Florida State University for a year. He joined the School of Engineering at University of Saint Thomas as an Assistant Professor in Fall 2009. His research interests include design and analysis of algorithms, evolutionary computation, wireless communications and networks, distributed sensor networks, and multi-objective optimization. He was awarded the Graduate School Masters Prize and the all university Doctoral Prize at Syracuse University in recognition of his research and scholarship. He has authored/co-authored conference and journal papers in the areas of wireless communications, sensor networks, and multi-objective optimization.