Networks of bio-nanomachines that communicate through molecular communication are expected to perform complex functionalities within biological systems. The natural history of malignant tumors can be defined by the evolution of growing bio-nanomachine networks within an interplay between proliferation or self-renewal (Grow) and invasion (Go) potential of mutually exclusive phenotypes. Herein we present a model of two populations of bio-nanomachines representing distinct phenotypes propagating throughout the progression of malignant gliomas within spatiotemporally evolving bionanomachine networks, driven by either attractive and linkforming or repulsive and cluster-forming forces. This model is further applied in computer simulations to examine the growth of bio-nanomachine networks in terms of size and network connectivity. Understanding the mechanisms by which malignant cells form bio-nanomachine networks and controlling network connectivity can contribute to deciphering mechanisms of tumor evolution and progression and provide new nanonetwork-based therapeutic approaches.

A bio-nanomachine network is useful in diverse applications of molecular communication. In this paper, we develop a network formation model of bio-nanomachines based on how vascular endothelial cells form a blood vessel-like structure. In our model, bio-nanomachines migrate toward each other using attractant molecules. When two bio-nanomachines move close to each other, they adhere to form a physical connection or a link between them. In this way, a group of bio-nanomachines forms a network collectively. We perform computer simulations using the model to identify critical parameter values at which a large-scale bio-nanomachine network emerges. The model developed in this paper helps us design synthetic communication networks of bio-nanomachines.

This paper provides a comprehensive review of the emerging research area of mobile molecular communication. In mobile molecular communication, sender and receiver bionanomachines as well as associated nodes in the environment exhibit dynamic behavior in the sense that they are mobile and communicate while they move. This paper presents a model of mobile bionanomachines and uses the model to discuss how groups of such bionanomachines working in unison can provide useful functionalities. This paper illustrates several functionalities by applying mobile molecular communication to the concept of cooperative drug delivery. Unsolved research challenges in this area are outlined and discussed.

Epidemic information dissemination is a promising technique for delivering messages in sparse mobile networks. This paper proposes an epidemic information dissemination method for mobile molecular communication systems by leveraging the mobility of bio- nanomachines. This paper first develops a mathematical model of epidemic information dissemination in mobile molecular communication systems, considering the detailed dynamics of information molecules, such as their spatial diffusion in the environment, their binding to bio-nanomachines, and their unbinding from bio-nanomachines. Using the mathematical model, we then conduct simulation experiments and show that the proposed method outperforms the existing methods where statically placed bio- nanomachines are used to relay information. Simulation results also show that the optimal moving speed of bio-nanomachines exists to minimize the propagation delay in the proposed method.

This paper proposes the leader-follower-amplifier-based model of mobile molecular communication systems for cooperative drug delivery. In the proposed model, system functionalities are divided and implemented onto three types of bio-nanomachine: leader, follower and amplifier bio-nanomachines. Leader bio-nanomachines are responsible for detecting targets, releasing attractant molecules and creating attractant gradients around the targets. Follower bio-nanomachines are responsible for carrying drug molecules and transporting through directed motion to the target locations. Amplifier bio-nanomachines are responsible for amplifying attractant molecules and enhancing attractant gradients created by leader bio-nanomachines. This paper first describes a design of the leader-follower-amplifier-based model. It then describes computer simulation models and numerical results to examine the performance of the proposed model.

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 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.

This paper considers mobile bionanosensor networks designed for target tracking in molecular environments. The mobile bionanosensor network considered in this paper consists of nano-to-microscale bio-nanomachines that coordinate their activity by propagating the two types of signaling molecules: attractants for a group of bio-nanomachines to move toward targets, and repellents to spread over the environment. A mathematical model for target tracking is developed and the performance of mobile bionanosensor networks is defined based on distributions of targets and bio-nanomachines. Numerical results are then shown to facilitate discussion of the impact of attractants and repellents on target tracking performance.

In molecular communication, a group of biological nanomachines communicates through exchanging molecules and collectively performs application dependent tasks. An open research issue in molecular communication is to establish interfaces to interconnect the molecular communication environment (e.g., inside the human body) and its external environment (e.g., outside the human body). Such interfaces allow conventional devices in the external environment to control the location and timing of molecular communication processes in the molecular communication environment and expand the capability of molecular communication. In this paper, we first describe an architecture of externally controllable molecular communication and introduce two types of interfaces for biological nanomachines; bio-nanomachine to bio-nanomachine interfaces (BNIs) for bio-nanomachines to interact with other biological nanomachines in the molecular communication environment, and inmessaging and outmessaging interfaces (IMIs and OMIs) for bio-nanomachines to interact with devices in the external environment. We then describe a proof-of- concept design and wet laboratory implementation of the IMI and OMI, using biological cells. We further demonstrate, through mathematical modeling and numerical experiments, how an architecture of externally controllable molecular communication with BNIs and IMIs/OMIs may apply to pattern formation, a promising nanomedical application of molecular communication.

In this paper, we consider multiple access in diffusion-based molecular communication where multiple bio-nanomachines transmit bits of information to a micro-scale receiver device in a shared environment. Each bio-nanomachine acting as a transmitter releases a molecule to send a Ί' and no molecule to send a ‘Ο’. The molecules released by transmitters then propagate by Brownian motion in the environment. The receiver device counts the number of molecules that arrived and estimates bits of information transmitted based on the number of molecules counted. A multiples access channel model is first developed to compute the capacity of the channel. Numerical results based on the model show that the channel capacity depends on various factors such as the number and location of transmitter bio-nanomachines.

In this paper, we discuss issues concerned with transmission rate control in molecular communication, an emerging communication paradigm for bio-nanomachines in an aqueous environment. In molecular communication, a group of bio-nanomachines acting as senders transmit molecules, the molecules propagate in the environment, and another group of bio-nanomachines acting as receivers chemically react to the molecules propagating in the environment. In the model of molecular communication considered in this paper, senders may transmit molecules at a high rate to accelerate the receiver reactions or to increase the throughput. However, if the senders transmit molecules faster than the receivers react, the excess molecules remain in the environment and eventually degrade or diffuse away, which results in loss of molecules or degradation in efficiency. Such a potential issue associated with throughput and efficiency is in this paper discussed as an optimization problem. A mathematical expression for an upper-bound on the throughput and efficiency is first derived to provide an insight into the impact of model parameters. The optimal transmission rates that maximize the throughput and efficiency are then numerically calculated and presented, and throughput and efficiency are shown to be in trade-off relationships in a wide range of transmission rates. Further, two classes of feedback-based transmission rate control schemes are designed for autonomous bio-nanomachines to dynamically control their transmission rates, respectively based on negative and positive feedback from the receivers. The numerical evaluation of the two transmission rate control schemes is then shown to provide useful guidelines for application developers to satisfy their design goals.

This paper focuses on throughput and efficiency of molecular communication between a pair of sender and receiver nanomachines. In the molecular communication considered in this paper, the sender transmits molecules at a fixed rate, the molecules propagate in the environment, and the receiver captures and processes the molecules following simple enzyme kinetics. We define throughput as the average number of molecules processed by the receiver per unit time, and efficiency as the throughput divided by the number of molecules transmitted by the sender per unit time. An upper bound on throughput and efficiency at steady-state are first derived. Simulation results are then provided to show that the throughput increases as the transmission rate increases and that the efficiency has an optimal transmission rate to achieve the maximum.

In this paper, we consider a nano-biosensor network composed of nano-to-micro scale biological machines distributed over a two-dimensional bounded area. The goal of the nano-biosensor network is to detect a target signal that propagates via Brownian motion in the monitoring area. Three simple nanomachine placement strategies are investigated: random, proportional, and regular placement. In the random placement, nanomachines are distributed randomly over the area. In the proportional placement, more nanomachines are placed where signals appear more frequently. In the regular placement, nanomachines are distributed to maintain a specific distance from adjacent nanomachines. Three placement strategies are evaluated through simulation based on the mean residence time which is defined as the average amount of time that a target signal stays in the monitoring area. Our simulation results show that the regular placement performs best when signal arrival locations follow normal distribution. Simulation results are also provided to show the impact of nanomachine failure on the mean residence time.

Molecular communication is a new paradigm for communication between biological nanomachines over a short-range (a nano- and micro-scale range). Biological nanomachines are nano- and micro-scale devices that either exist in the biological world or are artificially created from biological materials and that perform simple functions such as sensing, logic, and actuation. Molecular communication provides a mechanism for biological nanomachines to communicate information by propagating molecules that represent the information. Molecular communication is based on observations of existing biological systems which use molecules as communication carriers. With the advancement of current research in areas such as synthetic biology and bio-nanotechnologies, it may become relatively easy in the near future to develop systems of biological nanomachines communicating through molecules. In this paper, we present a framework for describing molecular communication systems.