Energy-driven computing for energy-harvesting embedded systems

There has been increasing interest over the last decade in the powering of embedded systems from ‘harvested’ energy, and this has been further fuelled by the promise and vision of IoT. Energy harvesting systems present numerous challenges, although some of these are also posed by their battery-powered counterparts: e.g. ultra-low power consumption. However, a significant challenge not witnessed in battery-powered systems is a requirement to manage the combination of a highly unpredictable and variable (spatially and temporally) power supply with a highly dynamic (across many orders of magnitude) and often event-driven system power consumption. This problem is typically rectified through the addition of energy storage (e.g. a supercapacitor) to provide energy buffering to smooth out the dynamics of supply and consumption. This has the significant advantage of making the system ‘look like’ a battery-powered system, yet usually adds volume, mass and cost to the resultant system – something that is counterproductive in future flexible, wearable and implantable IoT systems. Such systems can, alternatively, include only a very small amount (or even zero) energy-storage. Now, instead of the system’s operation being dictated solely by the application, operation starts to become ‘energy-driven’, with execution being highly intertwined with power and energy availability. In this presentation, I will first introduce the landscape of energy-harvesting computing systems, and articulate how energy-driven computing presents a different class of computing to conventional approaches. A significant issue in the successful operation of these systems is their ability to operate from an intermittent, constrained and variable supply, and I will show how transient operation and power-neutrality can be used to achieve the vision for these systems, and hence enable the proliferation of tiny self-powered systems that will underpin much of the IoT