Worst-Case Energy-Consumption Analysis by Microarchitecture-Aware Timing Analysis for Device-Driven Cyber-Physical Systems

Many energy-constrained cyber-physical systems require both timeliness and the execution of tasks within given energy budgets. That is, besides knowledge on worst-case execution time (WCET), the worst-case energy consumption (WCEC) of operations is essential. Unfortunately, WCET analysis approaches are not directly applicable for deriving WCEC bounds in device-driven cyber-physical systems: For example, a single memory operation can lead to a significant power-consumption increase when thereby switching on a device (e.g. transceiver, actuator) in the embedded system. However, as we demonstrate in this paper, existing approaches from microarchitecture-aware timing analysis (i.e. considering cache and pipeline effects) are beneficial for determining WCEC bounds: We extended our framework on whole-system analysis with microarchitecture-aware timing modeling to precisely account for the execution time that devices are kept (in)active. Our evaluations based on a benchmark generator, which is able to output benchmarks with known baselines (i.e. actual WCET and actual WCEC), and an ARM Cortex-M4 platform validate that the approach significantly reduces analysis pessimism in whole-system WCEC analyses