Wireless sensor networks (WSNs) with energy harvesting capabilities have drawn increasing attention in the last few years, as they enable long-term monitoring applications. However, the level of power harvested is usually limited to few mW. To improve the energy efficiency of WSNs, many power management techniques have been proposed to adjust the quality of service according to the harvested energy fluctuations. As wireless communications consume a major fraction of the available energy, numerous medium access control (MAC) protocols have been proposed to minimize energy consumption, latency, and data collisions. In this paper, we present an innovative MAC protocol for energy-harvesting based WSNs exploiting ultralow-power wake-up radios. To overcome the limited range typical of wake-up radios, a multi-hop wake-up scheme based on a dual radio system is proposed enabling asynchronous communications between a base station and any node of the network while maintaining a low latency and a high energy efficiency. To reduce energy consumption, wake-up calls and data packets are transmitted using two distinct data rates. Combined with destination address decoding, using a higher data rate for data transmission also minimizes the risk of collisions. Our approach has been applied to monitoring applications composed of autonomous sensor nodes powered by indoor light energy. OMNeT++ simulation results demonstrate the benefits of our wake-up radio-based approach in terms of energy, latency, and collisions when compared with the state-of-the-art duty-cycled MAC protocols. Experiments performed with real WSN platforms equipped with a wake-up radio prototype confirm the efficiency of our approach.

Wireless Sensor Networks (WSN) provide a powerful combination of distributed sensing, computing and wireless communication that can be useful in various applications (monitoring, health and fitness, environment, automotive, smart building, etc.). However, energy consumption is a critical issue in the deployment of battery-powered wireless sensor networks. Therefore, energy harvesting provides a potential solution to extend the system lifetime. This paper addresses the problematic of using wind as harvesting source, and weather forecast to improve the prediction of wind condition in the near future. The related issues concern the wind behavior in outdoor condition which is irregular and unpredictable. A wind harvester (a small wind turbine) is considered in order to define a model that translates a weather forecast (the wind speed) into a corresponding energy harvesting prediction. The proposed network architecture has therefore to manage the retrieval of weather forecast from Internet and transmit this information to the end devices. Moreover, the renewable energy storage device needs to be properly sized in order to provide power to the end devices when no more energy can be harvested from the ambient environment. For that, it is required to store a part of the harvested energy when it is available, and this is the role of a power manager (PM). In this paper, we propose different PM policies, two of them exploiting the use of weather forecast to improve the prediction accuracy for WSN nodes.

To design autonomous wireless sensor networks (WSNs) with a theoretical infinite lifetime, energy harvesting (EH) techniques have been recently considered as promising approaches. Ambient sources can provide everlasting additional energy for WSN nodes and exclude their dependence on battery. In this article, an efficient energy harvesting system which is compatible with various environmental sources, such as light, heat, or wind energy, is proposed. Our platform takes advantage of double-level capacitors not only to prolong system lifetime but also to enable robust booting from the exhausting energy of the system. Simulations and experiments show that our multiple-energy-sources converter (MESC) can achive booting time in order of seconds. Although capacitors have virtual recharge cycles, they suffer higher leakage compared to rechargeable batteries. Increasing their size can decrease the system performance due to leakage energy. Therefore, an energy-neutral design framework providing a methodology to determine the minimum size of those storage devices satisfying energy-neutral operation (ENO) and maximizing system quality-of-service (QoS) in EH nodes, when using a given energy source, is proposed. Experiments validating this framework are performed on a real WSN platform with both photovoltaic cells and thermal generators in an indoor environment. Moreover, simulations on OMNET++ show that the energy storage optimized from our design framework is utilized up to 93.86%.

In this paper, we propose a global power management approach for energy harvesting sensor nodes. Our approach is based on a joint duty-cycle optimization and transmission power control. By simultaneously adapting both parameters, the node can maximize the number of transmitted packets while respecting the limited and time-varying amount of available energy. We obtain a high-packet delivery by using an original predictive transmission power control that can efficiently adapt the transmission power to the wireless channel conditions. To accurately model the wireless channel and the node communication hardware, a waveform-level radio frequency simulator has been developed. Simulation results show 6.5 times improvement in energy efficiency and a packet reception ratio which is 9 times more efficient than a recently published technique. A 15% increase in energy efficiency, with respect to a fixed transmission power configuration, has also been observed. Finally, the global power management strategy has been validated on a real wireless sensor networks platform. Experimental results are very similar to those obtained in simulations, and thus confirm the efficiency of our power management approach.

Exploiting energy from the environment to extend the system lifetime of Wireless Sensor Network (WSN), especially thermal energy, is considered as a promising approach. When considering self-powered systems, the Power Manager (PM) plays an important role in energy harvesting WSNs. Instead of minimizing the consumed energy as in the case of battery-powered systems, it causes the harvesting node to converge to Energy Neutral Operation (ENO) in order to achieve a theoretically infinite lifetime. In this paper, a low complexity PM for a thermal-powered WSN is presented. Our PM adapts the duty cycle of the node according to the estimation of harvested energy and the consumed energy provided by a simple energy monitor for a super capacitor based WSN to achieve the ENO. Experiments are performed on a real WSN platform where harvested energy is extracted from the wasted heat of a PC adapter by two thermoelectric generators.