Performance Evaluation of Leader–Follower-Based Mobile Molecular Communication Networks for Target Detection Applications

TLDR

The study introduces a leader‑follower mobile molecular communication network for target detection, aiming to demonstrate functional division that facilitates design and development of such networks. The model partitions the network into leader bio‑nanomachines that detect targets and generate attractant gradients, and follower bio‑nanomachines that follow these gradients to reach targets and release drugs, with mathematical formulations, wet‑lab parameter estimation, and realistic simulations used to evaluate performance. The results offer insights into the application‑level performance of the proposed molecular communication network.

Abstract

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.