Self-organizing sensor networks designed as a population of mutually coupled oscillators

The mathematical models of populations of biological oscillators are a powerful tool for designing sensor networks with high energy efficiency, fault tolerance and scalability. Recently, Hong and Scaglione have proposed a novel design paradigm, based on pulse coupled oscillators, where the decision of each sensor is encoded as the time position of the emitted pulses. In this work, we propose an alternative approach, based on linear (not necessarily pulse) oscillators with nonlinear coupling, that provides a novel framework to design sensor networks that, in addition to the properties of distributed decision, self-synchronization, fault tolerance, scalability, and small complexity, allows for local information storage or information propagation, in analog form, through mutual coupling among nearby oscillators.