A case for opportunistic embedded sensing in presence of hardware power variability

The system lifetime gains provided by the various power management techniques in embedded sensing systems are a strong function of the active and sleep mode power consumption of the underlying hardware platform. However, power consumption characteristics of hardware platforms exhibit high variability across different instances of the platform, diverse ambient conditions, and over passage of time. The factors underlying this variability include increased manufacturing variations and aging effects due to shrinking transistor geometries, and deployment of embedded devices in extreme environments. Our experimental measurements show that large variability in sleep mode power is already present in commonly used embedded processors, and technology trends suggest that the variability will grow even more over time and affect active mode power as well. Such variability results in suboptimal lifetime and service quality. We therefore argue for energy management approaches that learn and model the power characteristics of the specific instance of the hardware platform, and adapt accordingly.