A simulation tool for nanoscale biological networks
Introduction
Nanonetworking is a new research area which consists of identifying, modeling, analyzing, and organizing communications at nanoscales [2]. It includes the design of communication protocols between devices in nanoscale environments, called nanomachines. Their goal is to expand the capabilities of nano-devices by allowing them to share information and cooperate. Since traditional communication models are not appropriate to represent nanonetworks, it is necessary to introduce new communication paradigms and technical solutions, such as suitable protocols and network architectures.
Nanomachines can be either biological or artificial devices. Different communication media may be present between them. For example, they may communicate through electromagnetic waves in the terahertz band, or by the exchange of ionized particles. Nanonetworks may provide new opportunities in various fields, from biomedical and environmental engineering, to military and industrial sectors (see [3], [2]). For example, biomedical applications may benefit from the use of nanonetworks for simplifying and enriching interactions among organs and tissues. Potential applications include the support to the immune system in fighting pathogens, the plant bio-hybrid systems for drug delivery and for health monitoring, and so on.
Research in nanonetworks is not mature yet, but several studies have already been made. Their results appear in both surveys [2] and specialized papers, particularly focused on molecular diffusion [20] and on the analysis of the noise sources in diffusion-based molecular communications [21]. In [12], the authors present NanoNS, a simulator for molecular diffusion based on the well-known NS-2, widely used for simulating classic wired and wireless networks. It is also worth citing the N3Sim initiative [18], [17], a Java simulator for molecular diffusion.
Given the variety of applications and types of nanonetworks, we have implemented a general tool for simulating different communication types at nanoscale. The aim of this work is to present this tool, from its design to its implementations aspects. It consists of a Java package able to provide a set of tools for simulating different nanoscale environments. The developed framework is general with respect to the application field, the types of nanomachines, the channel model, and the nanomachines mobility model. Thus, it can be easily specialized to model very different scenarios in extreme details.
In order to demonstrate the capabilities of our simulator, we show a simulation of a section of a lymph node. The simulation includes the information exchange during the humoral immune response between the antibody molecules produced by the immune system.
The paper is organized as follows. In Section 2 we illustrate the related work. In Section 3, we describe our simulator, by showing the relevant development strategy. In Section 4, we describe the simulated case study relevant to the immune system. This section includes some concepts on molecular communications, cell physiology, and immune system, essential for understanding the biological scenario of the simulations. In addition, we show the numerical results achieved by our simulator. Finally, in Section 5 we draw our conclusion and illustrate future directions of our research.
Section snippets
Nanonetworks studies
Several studies has been made on nanonetworks. Most of them regard the diffusion propagation model, typically based on the Brownian motion [9]. Some recent works have developed mathematical frameworks related to the diffusion-based particle exchange (i.e. particle emission, particle diffusion and particle reception), which is physical support for communications [20]. These models provide end-to-end evaluation of the normalized gain and delay as functions of the system frequency and transmission
The software library
The software library of our simulator was developed in Java. Its purpose is to provide a toolkit for simulating different types of nanonetworks. The initial step of its development was the identification of the main features of the communication mechanisms between nanomachines used in most scenarios. The analysis of requirements was done by considering the molecular communication assumed in some nanonetwork models, even if this approach does not hinder the possibility of simulating different
Molecular communications
Molecular communications is a new interdisciplinary research area including nanotechnology, biotechnology, and information and communication technologies. Exchanged information is encoded by using the specific molecules, typically through temporal variation of either molecule concentration in the propagation medium or molecule characteristics. A major difference between traditional networks and molecular nanonetworks is the propagation speed. Traditional networks, using electromagnetic waves,
Conclusions and future works
In this paper we have shown a simulation platform for nano-networks written in Java. The flexibility of this simulator has been demonstrated by simulating a biological nano-network. In particular, the study of the main elements of the immune system has allowed us to model the significant components of this nano-network.
Information is transferred upon carrier assimilation by cells. These carriers, which are the IL-4 cytokines, propagate through a fluidic medium from the transmitter, a basophil,
L. Felicetti received the master degree in Information and Telecommunication Engineering from University of Perugia in 2011. Now, he is a Ph.D. student at the Department of Electronic and Information Engineering, University of Perugia. His current research interests focus on nano-scale networking and communications.
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L. Felicetti received the master degree in Information and Telecommunication Engineering from University of Perugia in 2011. Now, he is a Ph.D. student at the Department of Electronic and Information Engineering, University of Perugia. His current research interests focus on nano-scale networking and communications.
M. Femminella received both the master degree and the Ph.D. in Electronic Engineering from University of Perugia in 1999 and 2003, respectively. Since November 2006, he has been Assistant Professor at the Department of Electronic and Information Engineering, University of Perugia. His current research interests focus on nano-scale networking and communications, middleware platforms for multimedia services, location and navigation systems, and network and service management architectures for the future Internet.
G. Reali has been an Associate Professor at the University of Perugia, Department of Information and Electronic Engineering (DIEI), Italy, since January 2005. He received the Ph.D. degree in Telecommunications from the University of Perugia in 1997. From 1997 to 2004 he was a researcher at DIEI. In 1999 he visited the Computer Science Department at UCLA. His research activities include resource allocation over packet networks, wireless networking, network management, and multimedia services.