Adapting task utility in externally triggered energy harvesting wireless sensing systems

Energy harvesting sensor nodes eliminate the need for post-deployment physical human interaction by using environmental power and wireless communication; however, they must adapt the utility of their tasks to accommodate the energy availability. For example, on sunny days, a solar-powered sensor node can perform highly accurate tasks requiring more extensive computation and communication, but on cloudy days, it must reduce utility due to a decrease in harvested energy. In this paper, we present a controller that uses two algorithms to balance task utility and execution time subject to an energy constraint. One algorithm determines the total execution time of a set of tasks such that desired task utilities are met, while the other solves the converse problem by approximating the maximum task utilities achievable within a global deadline. We apply our methods to a prototype Structural Health Monitoring system, demonstrating the controller's ability to adapt at runtime.