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Computing over Unreliable Networks

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Abstract:
In this talk, we take the unifying view of systems interacting over communication networks as distributed computing systems and propose to study them as networked control systems. We first show that a popular algorithm for distributed averaging can generate a collective global complex behavior associated with Lévy flights, when the inter-agent communication happens over unreliable links. To mitigate the effects of the unreliable information exchange, we present a distributed averaging algorithm based on control ideas resilient to noise and intermittent communication. The algorithm and the control perspective are the basis for the development of distributed optimization systems that we can analyze and design as networked control systems. In particular, we can design networked controllers to improve the performance of ad-hoc distributed optimization systems. We apply our approach to obtain distributed least squares solvers and distributed solvers of systems of linear equations, which are resilient to communication uncertainties. Finally will present an application of the approach to the distributed solution of the non-convex Optimal Power Flow problems.

Type of Seminar:
Control Seminar Series
Speaker:
Prof. Nicola Elia
Iowa State University
Date/Time:
Dec 05, 2016   17:15
Location:

ETZ E 8
Contact Person:

Sabrina Baumann
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Biographical Sketch:
Nicola Elia is a Professor of Electrical and Computer Engineering at Iowa State University. He received the Laurea degree in Electrical Engineering from Politecnico di Torino in 1987, and the Ph.D. degree in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in 1996. He worked at the Fiat Research Center from 1987 to 1990. He was Postdoctoral Associate at the Laboratory for Information and Decision Systems at MIT from 1996 to 1999. He has received the NSF CAREER Award in 2001. His research interests include networked control systems, communication systems with access to feedback, complex systems, distributed optimization and control.