אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

In the distributed average consensus problem, each node in a network has an initial value, and the objective is for all nodes to reach consensus at the average of these values using only communication with nearby nodes. Distributed average consensus algorithms have a wide variety of applications, including distributed optimization, sensor fusion, load balancing, and autonomous vehicle formation control.

This talk centers on the analysis of distributed averaging algorithms for consensus and vehicle formation control in networks with dynamic characteristics such as stochastic packet loss, node failures, network partitions, and additive disturbances. I will present an overview of distribued averaging algorithms and some recent results on the stability and robustness of these algorithms in dynamic networks. We analyze the relationship between algorithm performance and the size, dimension, and dynamic characteristics of the network, and we show that network dimension imposes fundamental limitations on algorithm performance in large networks.

bio: Dr. Stacy Patterson received her B.A in Mathematics and B.S. in Computer Science from Rutgers University in 1998 and her M.S. and Ph.D. in Computer Science from the University of California, Santa Barbara in 2003 and 2009 respectively. From July 2009 to August 2011, she was a postdoctoral scholar at the Center for Control, Dynamical Systems, and Computation at the University of California, Santa Barbara. She is currently a postdoctoral fellow in the Department of Electrical Engineering at the Technion, working with Professor Idit Keidar. Her research interests include distributed systems, vehicle networks, and cloud computing.