Distributed systems are comprised of multiple subsystems that interact in two distinct ways: (1) physical interactions and (2) cyber interactions; i.e. sensors, actuators and computers controlling these subsystems, and the network over which they communicate. A broad class of cyber-physical systems (CPS) are described by such interactions, such as the smart grid, platoons of autonomous vehicles and the sensorimotor system. This paper will survey recent progress in developing a coherent mathematical framework that describes the rich CPS “design space” of fundamental limits and tradeoffs between efficiency, robustness, adaptation, verification and scalability. Whereas most research treats at most one of these issues, we attempt a holistic approach in examining these metrics. In particular, we will argue that a control architecture that emphasizes scalability leads to improvements in robustness, adaptation, and verification, all the while having only minor effects on efficiency – i.e. through the choice of a new architecture, we believe that we are able to bring a system closer to the true fundamental hard limits of this complex design space.
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