Energy-Aware Task Scheduler for Self-Powered Sensor Nodes: from Model to Firmware

The self-powering paradigm surely represents a challenging issue in the Wireless Sensor Network (WSN) field. The chance of supplying the sen- sor node with environmental energy is attractive not only to make it au- tonomous and reduce the human intervention for battery substitution but also to improve the overall WSN flexibility and applicability. From this same perspective, a relevant role is played by the node task scheduling, which is required to face strong constraints due to energy availability limitations. On purpose, some of the authors have recently proposed an Energy-Aware ap- proach (namely Energy-Aware Lazy Scheduling Algorithm, EA-LSA), which shows a certain versatility in efficiently exploiting the harvested energy, re- ducing the starving occurrences in non-ideal conditions, with respect to the no-EA counterpart. In this work a task scheduler based on the EA-LSA technique has been implemented on a low-cost and commercially available platform, from Texas Instruments, with the aim to propose an open and easy-to-use HW/SW ref- erence for the community working in the field. The firmware, including the hardware abstraction and the scheduling routine layers, has been developed from scratch. Moreover, a few tasks have been developed so that the device activity could be simulated in a realistic scenario. To monitor the harvesting process an emulated energy harvester has been devised and included in the overall framework. The different task energy consumptions have been measured by means of an energy audit tool, specifically set up in order to properly gauge the very low current consumptions of the device. Experiments performed under different power income levels, allowed to positively conclude about the effectiveness of the implemented Energy-Aware scheduler, its flexibility in terms of environmental energy exploitation, and therefore its suitability for involvement in real-world WSNs.