Probabilistic data collection protocols for energy harvesting wireless sensor networks
International Journal of Ad Hoc and Ubiquitous Computing
| Hi-index | 0.00 |
Energy is the most limiting factor in wireless sensor networks. Harvesting solar energy is a feasible solution to overcome the energy-constraint in some applications. It enables a theoretically infinite network lifetime, sustaining a mode of operation termed energy neutral consumption rate. The challenge arises, how can the harvested energy be utilized to maximize the performance of the sensor network. Considering a field monitoring application the performance is measured as the sustained sampling rate of the sensors. Maximizing the sampling rate needs to take the spatio-temporal distribution of load and energy into account, to prevent the overloading of nodes. In [12] they introduced a optimal, theoretical solution based on perfect global knowledge. In this paper we propose the solar-aware distributed flow (SDF) approach. SDF enables each node to predict the harvested energy, calculate a sustainable flow and control its local neighborhood. Extensive simulations confirmed that SDF achieves over 80% of the theoretical optimum, while introducing negligible overhead.