Power/Energy Estimator for Designing WSN Nodes with Ambient Energy Harvesting Feature

Wireless Sensor Networks (WSNs) consist of spatially distributed autonomous sensors to cooperatively monitor physical conditions. Thus, the node battery autonomy is critical. To outperform it, most WSNs rely on the harvesting capability. As nodes can recharge whenever energy is available, the problem is to determine at design time the node autonomy. For our project, we solve it by creating a power/energy estimator that simulates business scenarios to predict node autonomy; the estimation concerns both power and energy features. Based on node architecture configuration, its Dynamic Power Management (DPM) policy, and environmental conditions, we present a simulator that helps identify power consumption hot spots and make critical choices during the system design. It also helps to scale the energy storage system as well as the energy harvesters correctly. The hardware part is modelled using the FLPA methodology to develop different node component models with a variable accuracy. For the logical part, we developped a specific DPM by integrating meteorology and weather forecast behaviours. The novelty comes from the ability to simulate the WSN harvesting capability and to estimate at runtime the remaining duration of each service.