Improving energy predictions in EH-WSNs with Pro-Energy-VLT

The increasing popularity of micro-scale energy-scavenging techniques for wireless sensor networks (WSNs) is opening new opportunities for the development of energy-autonomous systems. To sustain perpetual operations, however, environmentally-powered motes must adapt their workload to the stochastic nature of ambient power sources. Energy prediction algorithms, which forecast the source availability and estimate the expected energy intake in the near future, are precious tools to support the development of proactive power management strategies. In this work, we propose Pro-Energy-VLT, an enhancement of the Pro-Energy prediction algorithm that improves the accuracy of energy predictions, while reducing its memory and energy overhead.