NeTS: Small: Wireless Design for Fast M2M Control
University Of California-Berkeley, Berkeley CA
Investigators
Abstract
This project aims to explore the fundamental architectural considerations involved in designing/operating wireless networks for fast Machine to Machine (M2M) communication. Current ideas in the M2M space are fundamentally being driven by ``slow M2M'' applications like electricity-monitoring in the Smart Grid with their intellectual foundations coming from the now maturing field of wireless sensor networks. This project advances the field by addressing the high-performance case of industrial automation with tight real-time operating requirements and the demand for very high reliability. To do this, the project will be leveraging new mathematical and conceptual tools developed to understand decentralized control systems as well as modern approaches to doing multiterminal wireless networking that better exploit the full potential of the wireless medium. The techniques used in this project will span networking, control theory, information theory, wireless modeling, signal processing, and circuit implementation. Broadly speaking, the kind of "Fast M2M" technology that this project is developing has the potential to help invigorate the agile manufacturing sector of the economy. Easily reconfigurable wireless interconnection in the industrial setting could help high-skill manufacturing where the United States has a potential advantage over low-wage countries. In the course of developing this technology, the project will train students and postdocs in a way that encourages cross-fertilization of ideas between wireless communication, networking, circuit implementation, control theory, and information theory. These ideas will also be incorporated into courses, including new M.Eng. courses aimed at educating technical leaders for industry. This is the kind of non-siloed education that is essential for innovation in the future. The project will also broaden participation in the technical workforce by mentoring female graduate students.
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