Enabling environmentally-powered indoor sensor networks with dynamic routing and operation

Self-sustainable systems exploit the power sources in the environment (such as solar power) to maintain it's operations. Wireless sensor networks, one of the most popular applications of self-sustainable systems, may harvest environmental energy to sense and communicate. A key issue of self-sustainable sensor networks is that the power source varies constantly. Thus, it is important for the system to intelligently adjust the workload on each sensor to increase the network lifetime. In our work, we propose a dynamic routing and operation strategy for self-sustainable sensor networks. The system configuration is adjusted dynamically according to the amount of energy harvested at each sensor node. Our strategy aims to maximize the sampling and communication frequencies of each sensor while not compromising system sustainability. Experimental results indicate that our strategy enables the best system performance and a higher probability of self-sustainability compared to other baseline strategies.