Imperial College London > Talks@ee.imperial > Featured talks > Communication, Computation, and Control: Through the Lens of Information

Communication, Computation, and Control: Through the Lens of Information

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If you have a question about this talk, please contact Professor Peter Cheung.

In modern systems, information flows not only through the communication links, but also through the circuits that process it, and through the control agents that use it. In this talk, I will first identify and understand some of these flows of information, and then use this understanding to propose novel strategies to make these systems more efficient and secure.

For applications of short-distance communication, the power required to transmit information can be dominated by that required in the information-processing circuits. I will first analyze bottlenecks of information flows in simple circuit models to present novel fundamental bounds on this processing power. These bounds show that communicating near Shannon-capacity fundamentally requires large encoding/decoding power. For minimizing total power at short distances, one should therefore use codes that operate far from Shannon capacity. I will complement this theoretical observation with our experimental work in circuits and code design. What can understanding circuit information flows tell us about securing communication systems? The presence of an eavesdropper in inductively-coupled links disturbs the circuit information flow. Based on this observation, I will present a secure communication scheme in which capacity-approaching codes are used to destroy the information leaked to an eavesdropper. However, because our scheme requires near-capacity communication, it in turn requires increased processing power.

In cyber-physical systems, information flows not only through the “cyber” links that connect different agents, but also implicitly through the “physical” plant being controlled. In order to understand these implicit information flows, I will focus on the minimalist problem of implicit communication—the Witsenhausen counterexample—that has been open for more than 40 years. By analyzing information bottlenecks for implicit communication, I will present the first approximately-optimal solutions to the Witsenhausen counterexample. I will then show that at the cost of reduced efficiency, these implicit information flows can be used to detect data-injection attacks.

Biography: Pulkit Grover (Ph.D. UC Berkeley) is a postdoc at Stanford University. He is interested in interdisciplinary research directed towards developing a science of information in order to make decentralized systems (from low-power communication systems to large cyber-physical systems) efficient, secure, and stable. Dr. Grover is the recipient of the best student paper award at the IEEE Conference in Decision and Control (CDC) 2010. For his dissertation research, he received the 2011 Eli Jury Award from the Department of EECS at UC Berkeley.

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