Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy.
Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), 43124 Parma, Italy.
Sensors (Basel). 2021 Nov 18;21(22):7664. doi: 10.3390/s21227664.
The complexity of molecular communications system, involving a massive number of interacting entities, makes scalability a fundamental property of simulators and modeling tools. A typical scenario is that of targeted drug delivery systems, which makes use of biological nanomachines close to a biological target, able to release molecules in the diseased area. In this paper, we propose a simple but reliable receiver model for diffusion-based molecular communication systems tackling the time needed for analyzing such a system. The proposed model consists of using an equivalent markovian queuing model, which reproduces the aggregate behavior of thousands of receptors spread over the receiver surface. It takes into account not only the fact that the absorption of molecules can occur only through receptors, but also that absorption is not an instantaneous process and may require a significant time during which the receptor is not available to bind to other molecules. Our results, expressed in terms of number of absorbed molecules and average number of busy receptors, demonstrate that the proposed approach is in good agreement with results obtained through particle-based simulations of a large number of receptors, although the time taken for obtaining the results with the proposed model is an order of magnitudes lower than the simulation time. We believe that this model can be the precursor of novel class of models based on similar principles that allow realizing reliable simulations of much larger systems.
分子通信系统的复杂性涉及大量相互作用的实体,使得可扩展性成为模拟器和建模工具的基本特性。一个典型的场景是靶向药物输送系统,它利用接近生物靶标的生物纳米机器,能够在患病区域释放分子。在本文中,我们提出了一种简单但可靠的基于扩散的分子通信系统接收机模型,用于分析这种系统所需的时间。所提出的模型包括使用等效马尔可夫排队模型,该模型再现了分布在接收机表面的数千个接收器的总体行为。它不仅考虑了分子只能通过受体吸收的事实,还考虑了吸收不是一个瞬时过程,可能需要很长时间,在此期间受体无法与其他分子结合。我们的结果以吸收的分子数量和平均忙碌受体数量表示,表明所提出的方法与通过大量受体的粒子模拟获得的结果非常吻合,尽管使用所提出的模型获得结果所需的时间比模拟时间低几个数量级。我们相信,这种模型可以作为基于类似原理的新型模型的先驱,从而实现对更大系统的可靠模拟。