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The functions required of real-time systems in the future such as the ability to see or hear, understand and react to external stimulus and the environment in much the same way that humans do, will force underlying communication and computing platforms to operate across very large changes in instantaneous workload. Supporting such workload variations on resource-constrained mobile systems will require new design approaches that cut across the traditional boundaries between the processing, mixed-signal, wireless, and sensor/ actuator (physical) domains, as well as the layers of each domain, i.e. circuit, architecture, algorithm, and application. Due to components fabricated in aggressive nanoscale technologies, such cyber-physical systems must deal with the impact of manufacturing process variations and component failures as well as different environmental conditions (temperature, noise environment) while operating in the most reliable manner with respect to mission goals. An integrated approach to designing such systems that utilizes real-time, cross-domain control and adaptation to operate the system at an “optimal” point that minimizes power consumption while meeting error resilience and performance constraints across different workloads and operating environments is proposed. The core strategy relies on the design and use of tunable algorithms, tunable architectures and tunable circuits that have the capability to trade off power vs. performance. Adaptation is performed by sensing the operating environment and workload using hardware and software “sensors” and dynamically tuning the system via an optimal control law. A critical observation is that this control law depends on the health of the system when power minimization is a key objective. The core ideas are demonstrated using a video surveillance system as a test case.