This paper proposes a leader-follower-based model of mobile molecular communication networks for target detection applications. The proposed model divides the application functionalities of molecular communication networks into two types of mobile bio-nanomachine: leader and follower bio-nanomachines. Leader bio-nanomachines distribute in the environment to detect a target and create an attractant gradient around the target. Follower bio-nanomachines move according to the attractant gradient established by leader bio-nanomachines; they approach the target and perform necessary functionalities, such as releasing drug molecules. This paper develops mathematical expressions for the proposed model, describes wet laboratory experiments designed to estimate model parameters, and performs biologically realistic computer simulation experiments to evaluate the performance of the proposed model. The main contributions of this paper are to demonstrate the functional division of molecular communication networks, which will facilitate the design and development of molecular communication networks. Furthermore, insight into the application-level performance of molecular communication networks will be provided based on the proposed model.

This paper describes a model of multi-target detection and gravitation by hypothetical microscale bioparticles. These bioparticles are capable of basic micro-scale communication based on established behavior observed in bacterial communities in nature. The bioparticles seek to distribute in the environment and secrete 'attractant' and 'repellent' molecules upon detecting targets. The attractant and repellent molecules secreted at targets freely diffuse to form concentration gradients in the environment, inducing population-dependent gravitational forces toward the targets. Simulation results presented in this paper show how model parameters affect the resulting distribution of bioparticles according to a given target distribution. Simulation results also show that, when model parameters are properly tuned, bioparticles express the ability to distribute evenly over targets.

This paper describes non-diffusion-based molecular communication and its application to an inbody mobile bionanosensor network. In the inbody mobile bionanosensor network, bio-nanomachines migrate in the environment while they release adhesive molecules that bind to a surface in the environment. The concentration gradient of adhesive molecules is thus formed over the surface, and bio-nanomachines migrate based on the gradient to coordinate their behavior. In the non-diffusion-based molecular communication, the formation of concentration gradient of adhesive molecules relies on the mobility of bio-nanomachines and thus the effective communication range may be limited. However, the non-diffusion-based molecular communication can maintain a high and stable concentration of molecules in the environment, allowing bio-nanomachines to detect the concentration to coordinate their behavior. Through mathematical modeling and performance evaluation, this paper demonstrates that the non-diffusion-based molecular communication may apply to induce coordinated behavior among mobile bio-nanomachines in the inbody environment considered in this paper.