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.

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 provides the author’s personal retrospective on molecular communication research. The author has been involved in molecular communication from its conceptualization to the establishment as a scientific discipline and its flourishing today. Based on his personal journey, the author describes the history of molecular communication research and shares what he learned from the journey. The author also discusses what might help for the further development of molecular communication research and points out technical challenges that he would like to see addressed in the next decade.

This letter presents a mathematical model of molecular communication networks where mobile bio-nanomachines coordinate their motion by using non-diffusive surface-bound molecules for detecting and localizing spatially distributed targets in the environment. The mathematical model assumes that bio-nanomachines release two types of molecule: repellents to distribute bio-nanomachines in search of targets and attractants to attract distributed bio- nanomachines toward target locations. The two types of molecule assumed in this letter are non-diffusive, meaning that molecules bind to a surface in the environment, creating concentration gradients on the surface in order to distribute bio-nanomachines according to the target distribution. In this letter, we first develop dimensionless equations for the non-diffusion-based mobile molecular communication networks. We then perform mathematical analysis to show that, at steady-state, bio- nanomachines distribute according to a given target distribution. Finally, we demonstrate through numerical experiments that the bio-nanomachine distribution converges to the steady-state solution.

The authors of this paper have been involved in molecular communication since its conception. The authors describe their decade-and-a-half long personal journey of the molecular communication research and share their observations and thoughts on how the molecular communication research started and expanded to flourish. They also share their thoughts on research challenges that they hope the molecular communication research community addresses in the coming decade.

We propose a new computing-inspired bio-detection framework called touchable computing (TouchComp). Under the rubric of TouchComp, the best solution is the cancer to be detected, the parameter space is the tissue region at high risk of malignancy, and the agents are the nanorobots loaded with contrast medium molecules for tracking purpose. Subsequently, the cancer detection procedure (CDP) can be interpreted from the computational optimization perspective: a population of externally steerable agents (i.e., nanorobots) locate the optimal solution (i.e., cancer) by moving through the parameter space (i.e., tissue under screening), whose landscape (i.e., a prescribed feature of tissue environment) may be altered by these agents but the location of the best solution remains unchanged. One can then infer the landscape by observing the movement of agents by applying the “seeing-is-sensing” principle. The term “touchable” emphasizes the framework’s similarity to controlling by touching the screen with a finger, where the external field for controlling and tracking acts as the finger. Given this analogy, we aim to answer the following profound question: can we look to the fertile field of computational optimization algorithms for solutions to achieve effective cancer detection that are fast, accurate, and robust? Along this line of thought, we consider the classical particle swarm optimization (PSO) as an example and propose the PSO-inspired CDP, which differs from the standard PSO by taking into account realistic in vivo propagation and controlling of nanorobots. Finally, we present comprehensive numerical examples to demonstrate the effectiveness of the PSO-inspired CDP for different blood flow velocity profiles caused by tumor-induced angiogenesis. The proposed TouchComp bio-detection framework may be regarded as one form of natural computing that employs natural materials to compute.