Stochastic analytical model of nanonetwork synchronization using quorum sensing

Abstract

A coordinated bacterial nanonetwork could be applicable to large and diverse application areas including nanomedicine, nanobiotechnology, green-nanoproducts, and so on. For the construction of a bio-inspired coordinated bacterial molecular communication (MC) nanonetwork, synchronization technique is essential. This paper presents a stochastic analytical model of the nanonetwork synchronization using quorum sensing (QS). The QS mechanism that controls bacterial behavior in a collective manner is often observed in bacterial community. Bacteria use secreted chemical signaling molecules called autoinducers (AI) to communicate with each other. For more practical analysis, the presented bacterial network model employs a birth death-based statistical approach with a logistic growth curve (S curve) instead existing deterministic approach with an exponential growth curve (J curve). Assume that the internal or external AI concentration is Gaussian-distributed with corresponding mean and variance. Via simulation, we analyze the global synchronization behavior of the presented bio-inspired nanonetwork in terms of synchronization time, bacterial density, and AI concentration.