Modeling and power optimization of cyber-physical systems with energy-workload tradeoff

In this paper, we propose to take the relationship between delay and workload into account in the optimization of cyber-physical systems (CPSs). Since the components at the physical side continuously change their values or properties, a longer delay at the cyber part may result in a bigger workload for the next computation. We formulate this tradeoff and apply it to the power optimization of CPS. In doing so, we examine the schedulability of the given CPS with respect to the given parameters and initial workload. Then, we propose to keep the system operate in the stable state with minimum scaling factor and prove that it is better than any alternating sequences. We verify the validity of the proposed delay-workload model by measuring the execution delay of real-life examples. The effectiveness of the proposed power optimization policy is demonstrated with simulation results.