Neuronal signaling optimization for intrabody nanonetworks

This paper considers natural neurons as a physical communication medium and defines a Time Division Multiple Access (TDMA) communication protocol on top of the physical layer to construct intrabody nanonetworks, each of which networks nanoscale nodes to perform sensing and actuation tasks in the body for biomedical and prosthetic purposes. The proposed protocol, called Neuronal TDMA, leverages a novel evolutionary multiobjective optimization algorithm (EMOA) to seek the optimal signaling schedule for individual nodes in the network with respect to conflicting optimization objectives such as signaling delay and fairness while avoiding signal interference. Simulation results show that the proposed EMOA efficiently obtains quality TDMA signaling schedules and outperforms existing EMOAs.