Molecular communication provides communication and networking capabilities for nanomachines such as biosensors and bio-actuators to form and enable Body Area NanoNetworks (BANNs). This paper considers neuron-based molecular communication, which utilizes natural neurons as a primary component to build BANNs, and proposes an end-to-end software architecture to manage and control neuron-based BANNs through a series of software services. Those services aid to realize end user applications in healthcare, such as biomedical and rehabilitation applications. In the proposed architecture, a neuron-based BANN consists of a set of nanomachines and a network of neurons that are artificially formed into a particular topology. This paper investigates two mechanisms in the proposed architecture: (1) an artificial assembly method to form neurons into specific three-dimensional topology patterns and (2) a communication protocol for neuronal signaling based on Time Division Multiple Access (TDMA), called Neuronal TDMA. The assembly method uses silica beads as growth surface and bead-bead contacts as geometrical constraints on neuronal connectivity. A web lab experiment verifies this method with neuronal hippocampal cells. Neuronal TDMA leverages an evolutionary multiobjective optimization algorithm (EMOA) to optimize the signaling schedules for nanomachines. Simulation results demonstrate that the Neuronal TDMA efficiently obtains quality solutions.
- Evolutionary multiobjective optimization algorithms
- Intrabody Nanonetworks
- Molecular communication
- Neuronal signaling