Energy and power awareness in hardware schedulers for energy harvesting IoT SoCs

Abstract

The recent growth of applications in the emerging Internet of Things field is posing new challenges in the long-term deployments of sensing devices. Currently, system designers rely on energy harvesting to reduce battery size and extend system lifetime. While some system functions need constant power supply, others can have their service adapted dynamically to the available harvested energy and harvesting power. Our proposed Torpor is a power-aware hardware scheduler which continuously monitors harvesting power and in combination with its software runtime, dynamically activates system functions depending on the available energy and its rate of change. By performing a few key functions in hardware, Torpor incurs a very low power overhead during continuous monitoring, while the software runtime provides a high degree of flexibility to enable different scheduling policies. We implemented Torpor on a FPGA-based prototype and demonstrated that dynamic scheduling policies which take the harvesting power into account can have a 2× or more improvement in execution rates compared to static (input-power-independent) policies, while dynamic policies that are aware also of the system's power consumption can achieve 1.5× improvement in the execution rates compared to the ones that do not. The power consumption of Torpor's always-on hardware integrated on chip is estimated to be less than 4 μW, making it a very promising power-management add-on for microprocessors used in IoT nodes.