The increasing use of electric vehicles (EVs) has highlighted the need for sustainable recycling and traceability of essential raw materials. This study introduces a blockchain and AI-integrated framework designed with the possibility to optimize vehicle components lifecycle management with recycling and tracing throughout the supply chain. The system uses Decentralized Identifiers (DIDs) for secure identification of components, enabling transparent tracking from production to recycling. Hyperledger Fabric ensures immutable data an choring across stakeholders. Hyperledger Caliper is used for benchmarking the system, assessing metrics such as transaction speed, latency, and scalability. AI models, including regression and clustering algorithms, are utilized to optimize recycling processes, predict component lifespans, and enhance resource recovery in the system. A tokenized reward mechanism incentivizes eco-friendly practices among stakeholders. The system also shows its environmental benefits, including energy savings from improved recycling performance. The proposed framework effectively supports the circular economy by enhancing resource recovery processes. While its design has the potential to reduce environmental impact, this benefit depends on the reusable, modular system design.

The Cellular Potts Model (CPM) is a powerful computational framework for simulating collective cell behavior, including morphogenesis, cell migration, and tissue dynamics. However, conventional CPM implementations rely on a sequential Modified Metropolis Algorithm (MMA), making large-scale simulations computationally expensive. In this work, we present a parallel boundary-based algorithm that accelerates CPM simulations by restricting copy attempts to boundary sites (i.e., lattice sites located at cell-cell or cell-substrate interfaces). Our algorithm combines local energy evaluation with a thread-safe parallelization strategy in which multiple threads independently assess copy attempts, while a central core thread applies accepted updates sequentially to ensure consistency. Benchmark results demonstrate a significant reduction in computation time compared to conventional implementations, enabling efficient simulation of larger and more complex cellular systems.

The rapid evolution of digital identity verification demands solutions that balance security, privacy, and efficiency. The electronic know your customer (eKYC) is a technological integration for client identification. It automates the process, reducing costs related to traditional know your customer (KYC). This includes eliminating paper-based document management, reducing manpower needs, and minimizing human errors. This systematic literature review (SLR) uses the preferred reporting items for systematic reviews and meta-analyses (PRISMA) model to investigate the revolutionary potential of blockchain-based electronic KYC (eKYC), focusing on self-sovereign identity (SSI) and Decentralized Identifiers (DID). The evaluation summarizes the current state by critically assessing 44 selected research works from an initial pool of 367. Our findings show that decentralized eKYC improves security with tamper-proof credentials and cryptographic verification. SSI and DID give users control over their data and selective disclosure. However, there are key limitations: 1) a focus on financial applications, ignoring Internet of Things (IoT) integration; 2) a lack of comprehensive technical analysis on scalability and interoperability; and 3) limited real-world case studies on regulatory compliance and challenges. This work combines insights from research and industry, highlighting the need for regulatory collaboration, hybrid architectures for scalability, and user-centric design. In addition, most identity management solutions are based on Ethereum (33%), followed by Hyperledger (18%). Around 51% of solutions use smart contracts, with banking (23%) and the financial industries (19%) being the primary adopters. It emphasizes the importance of standardized eKYC protocols, technical evaluations, and interdisciplinary collaboration for practical adoption across sectors.

This paper demonstrates experimentally that spatially distributed cell clusters grow their branches and form a molecular communication network. This paper also develops a computational model of cells to understand the biophysical mechanisms by which cell clusters grow. In the model, cells form a cluster using attractive and repulsive forces. Cells then change their state to be leaders or followers, depending on the number of cells with which the cells are in physical contact. Those cells that become leaders use forward forces and move away from the cluster while those that become followers use following forces to follow their leaders. Through the interplay between leaders and followers, the cluster creates and grows its branches. We conduct computer simulations using the computational model and understand how the model parameters affect the number and length of branches that the cluster creates and grows. The computational model and simulation results described in this paper will help understand how spatially distributed cell clusters grow and eventually form a synthetic molecular communication network.

Creating a large-scale functional structure from a group of bio-nanomachines is key for engineering applications of molecular communication. This paper aims to create a large-scale functional structure from a group of bio-nanomachines, and proposes a collective rotational motion model of bio-nanomachines. In the proposed model, a group of bio-nanomachines forms a cluster that continues to rotate. The proposed model is based on the idea that spinning objects are stable against perturbations. In developing the model, we draw inspiration from biological pattern formation: biological entities interact chemically and physically to form a functional structure. Accordingly, we develop a collective rotational motion model based on chemical and physical interactions between bio-nanomachines. Through modeling and simulations, we gain insight into design and engineering of rotating clusters of bio-nanomachines. This paper demonstrates the importance of physical interactions in creating a system-level functionality from a group of bio-nanomachines, giving rise to new challenges and opportunities in molecular communication research.

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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.

In this paper, we propose a model of how bio-nanomachines differentiate their functionality in molecular communication. In the proposed model, bio-nanomachines perform a set of basic functions such as releasing signal molecules into the environment, detecting the concentration of signal molecules in the environment, and migrating toward the higher concentration of signal molecules, while they acquire energy from the environment and consume energy to perform such functions. The net amount of energy (total energy acquired minus total energy consumed) of a bio-nanomachine reflects what functions it performed and how actively it performed such functions and indicates how it will differentiate itself from other bio-nanomachines in performing functions. Simulation results show that bio-nanomachines starting with the same amount of net energy come to have different amounts of net energy and, as a result, differentiate and form a complex spatial distribution of bio-nanomachines. The proposed model helps understand how bio-nanomachines differentiate and acquire complex functionalities in molecular communication.

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.

Calcium signaling plays an important role in both physiological activities and engineered applications of molecular communication. Recent experimental studies in biology reveal that calcium signaling is closely related to mobility of biological cells. In this paper, we address communication-related issues of calcium signaling among a group of mobile cells. First, a mobility model of biological cells is established based on experimental studies in biology. Then, the mobility model is integrated with a widely accepted model of calcium signaling. Further, computer simulations are performed using the integrated model to examine the communication-related performance of calcium signaling among a group of mobile cells. A major finding from computer simulations is that there exists an optimal moving velocity of cells to maximize the range of signal propagation in a group of mobile cells.

In this paper, we consider kinesin molecular motors transporting a bead over a network of microtubules and develop mathematical models to describe the stochastic behavior of kinesins carrying a bead. In developing the mathematical models, we consider the kinesins' stochastic behavior (1) at an intersection of crossing microtubules to obtain the probabilities of pass, switch, pause and dissociate stochastic behaviors of the kinesins carrying a bead and (2) over a network of microtubules through multiple microtubule intersections to obtain transition probabilities for kinesins carrying a bead starting from a given sender to reach a given receiver in the network. We examine the accuracy of the developed mathematical models using in vitro experimental results in our previous work.

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 presents a biologically inspired design and its implementation of macroscale mobile molecular communication systems. Our design of macroscale mobile molecular communication systems consists of a statically placed target and mobile nodes that autonomously move in the environment. The target keeps releasing molecules to create a concentration gradient in the environment, and mobile nodes sense the concentration gradient in the environment and move toward the target according to an algorithm inspired by bacterial chemotaxis. The proposed design of macroscale molecular communication systems is implemented using electrical sprays, mobile robots and alcohol molecules, and evaluated experientially. The proposed design and implementation provides a new tool to study mobile molecular communication systems.

In this paper, we discuss the design and implementation of a novel telecommunication system, the avatar-mediated communication (AMC) system, for constructing interpersonal relationships. In the AMC system, human users develop conversation experiences through software agents without directly interacting with their conversation partners. We develop an experimental platform for human users to control software agents to interact with their conversation partners and examine how their actions of controlling the software agents and consequences led by the software agents contribute to the development of their conversation experiences and interpersonal relationships. Experimental results demonstrate that actions are not important; however, consequences are important. The result sets a basis for the design and implementation of future AMC systems.

Molecule loss is a critical reliability issue in diffusive molecular communications. This paper proposes a communica- tion framework that allows biologically-enabled machines (bio- nanomachines) to transmit and receive information-carrying molecules (information molecules) in a robust manner against molecule losses. The proposed framework, called molecular fountain, employs deoxyribonucleic-acid (DNA) molecules as information carriers and leverages molecular fragmentation (i.e., packetization) between transmitter (Tx) and receiver (Rx) bio-nanomachines. It performs feedback-aided rateless erasure coding that considers biochemical constraints in DNA synthesis and sequencing to generate molecular packets. The Tx bio- nanomachine repeatedly generates molecular packets with Luby transform codes and transmits them to the Rx bio- nanomachine until it receives an acknowledgment from the Rx bio-nanomachine. The Rx bio-nanomachine can reconstruct lost molecular packets from other packets that have been successfully transmitted. Simulation results show that molecular fountain enhances robustness against molecular packet losses and in turn improves communication performance such as transmission latency, jitter, error rate, and coding overhead.

Switching is an indispensable functionality in traditional computer networks. Inspired by computer networks design, this paper investigates the switching functionality for molecular communication networks. In particular,we design channel switches for molecular communication among biological cells through calcium signaling. First, we extend mathematical models of calcium signaling by incorporating gating models of gap junction channels. Second, we show how channel switches may be designed based on the mathematical models, with numerical results demonstrating the switching functionality. Further, we discuss design issues for practical application of channel switches. This paper shows through mathematical modeling and numerical experiments that channel switches are feasible and indicates that complex molecular communication networks may be designed using channel switches.

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 explores the dynamic properties of oscillating and propagating patterns in concentration of the information molecule and proposes a new modulation scheme for molecular communication. In the proposed modulation scheme, information molecules transmitted from a sender bio-nanomachine propagate in the environment, chemically react with the molecules in the environment, change their concentration, and form an oscillating and propagating pattern in the environment. A sender bio-nanomachine modulates information onto the dynamic properties of the pattern, such as the amount of change in concentration of the information molecule and the time duration of one cycle of a periodic pattern in concentration of the information molecule. Receiver bio-nanomachines receive the oscillating and propagating pattern that the sender bio-nanomachine generates and detect its dynamic properties to demodulate information. This paper implements the proposed modulation scheme using Ca2+oscillation and propagation, a communication mechanism found in biological cells. It also demonstrates that the proposed modulation scheme allows information to be simultaneously modulated onto multiple dynamic properties of an oscillating and propagating pattern that a sender bio-nanomachine generates. The main contributions of this paper are to open a new research area of modulation schemes in molecular communication and to illustrate the possibility that biological cells use such modulation schemes for cell-to-cell communication.

This paper describes a model of multi-target detection and gravitation by hypothetical microscale bioparticles. These bioparticles are capable of basic micro-scale communication based on established behavior observed in bacterial communities in nature. The bioparticles seek to distribute in the environment and secrete 'attractant' and 'repellent' molecules upon detecting targets. The attractant and repellent molecules secreted at targets freely diffuse to form concentration gradients in the environment, inducing population-dependent gravitational forces toward the targets. Simulation results presented in this paper show how model parameters affect the resulting distribution of bioparticles according to a given target distribution. Simulation results also show that, when model parameters are properly tuned, bioparticles express the ability to distribute evenly over targets.

This paper proposes a novel design of reliable end-to-end molecular communication. In molecular communication proposed in this paper, source and destination bio-nanomachines exchange molecular packets through intermediate bio-nanomachines. A source bio-nanomachine forms a molecular packet and transmits the molecular packet into the environment. An intermediate bio-nanomachine detects a molecular packet and produces its copies. A destination bio-nanomachine, upon reception of a molecular packet, produces an acknowledgment molecular packet and transmits back to the source bio-nanomachine. Further, a source bio-nanomachine retransmits a molecular packet if no acknowledgment molecular packet is returned within a time-out period. In this paper, we develop an analytical framework to study propagation delay in the reliable end-to-end molecular communication proposed in this paper. We also show how the proposed molecular communication is biochemically implemented using ribonucleic acid (RNA) molecules.

This paper proposes to use spatio-temporal patterns that the concentration of propagating information molecules form in the molecular communication environment and develops a new modulation technique for molecular communication between bio-nanomachines. In molecular communication considered in this paper, information molecules transmitted from a group of sender bio- nanomachines propagate in the environment, chemically react with the molecules in the environment, change their concentration, and form an oscillating and propagating pattern. The rates at which sender bio-nanomachines transmit information molecules determines the frequency, amplitude and phase characteristics of the pattern, and the sender bio-nanomachines modify the transmission rates in order to modulate information on to frequency, amplitude and phase characteristics of the pattern. A group of receiver bio-nanomachines detects these characteristics to collectively decode information. This paper develops a new model of molecular communication through pattern formation. Using the model developed in this paper and numerical examples, this paper demonstrates the advantages of the proposed modulation technique, namely, higher information capacity and longer communication distances.

This paper considers short-range (up to 100 μm) molecular communication where bio-nanomachines transmit and receive molecule-encoded messages and applies Stop-and-Wait Automatic Repeat Request (SW-ARQ) for feedback-based reliable communication in noisy intrabody environments. Three coommunication transports are considered: (1) diffusive transports where molecules diffuse via random thermal motion, (2) directional transports where molecules directionally move on pre-defined protein filaments with molecular motors and (3) diffusive-directional hybrid transports where molecules propagate with both diffusive and directional transports. Simulation results demonstrate that SW-ARQ improves latency and reliability in both diffusive and directional transports. Hybridization of the two transports aids extra improvements in latency and reliability.

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 this paper, we present a communication protocol between a pair of biological nanomachines, i.e., a transmitter and a receiver, built upon molecular communications in an aqueous environment. In our proposal, the receiver, acting as a control node, sends a connection setup signal to the transmitter, which stokes molecules, to start molecule transmission. The molecules transmitted by the transmitter propagate in the environment and are absorbed by the receiver through its receptors. When the receiver absorbs the desired quantity of molecules, it releases a tear-down signal to notify the transmitter to stop the transmission. The proposed protocol implements a bidirectional communication by using a number of techniques originally designed for the TCP. In fact, the proposed protocol is connection-oriented and uses the TCP-like probing to find a suitable transmission rate between the transmitter and the receiver to avoid receiver congestion. Unlike the TCP, however, explicit acknowledgments are not used since they would degrade the communication throughput due to the large delay, which is a characteristic feature of molecular communications. Thus, the proposed protocol uses implicit acknowledgments, and feedback signals are sent by the receiver to throttle the transmission rate at the transmitter, i.e., explicit negative feedback. We also present the results of an extensive simulation campaign, used to validate the proposed protocol and to properly dimension the main protocol parameters.

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.

Systems of distributed nanomachines are an anticipated paradigm for future interaction with biological systems. Future applications for systems of distributed nanomachines require nanomachines to coordinate among themselves as well as interact with larger-scale systems such as medical or environment devices. One potential technique to communicate with distributed nanomachines is through molecular communication. For example, a nanomachine transmits pulses of a type of molecule to represent bits of information and a device (i.e. may be either a nano-scale or larger-scale device) decodes information from the concentration characteristics of the type of molecule. In this paper, we consider multiple transmitters multiplexing bits of information to a micro-scale receiver using the same type of molecule. Concentration of the type of molecule depends on the bits transmitted and the distances to the transmitters. We model the concentration detected by the receiver to measure the expected number of bits per transmission interval.

This paper investigates, through computer simulations, statistical behavior of molecular motors transporting cargos on a network of protein filaments in an engineered environment. This paper also examines how molecular motors' statistical behavior is applied to building. a molecular communication system. A molecular motor, such as kinesin, is a protein complex. It exists in eukaryotic cells and functions as a nano-scale autonomous nanomachine that carries nano-scale to micro-scale signaling molecules on a network of protein filaments (i.e., cytoskeletal network) in eukaryotic cells. At an intersection of protein filaments on a cytoskeletal network, a molecular motor shows stochastic movement and may stay on the current protein filament or may switch onto an intersecting protein filament, resulting in stochastic delivery of signaling molecules from the nucleus to organelles over a cytoskeletal network. Molecular communication is an engineered system to transmit information by modulating information on molecules and by transporting modulated molecules from senders to receivers. One of promising approaches to building a molecular communication system is to use molecular motors to transport information-modulated molecules on an engineered protein filament network connecting senders and receivers. In order to examine the feasibility of this approach, this paper simulated statistical behavior of molecular motors carrying cargo molecules through multiple protein filament intersections on a protein filament network. Simulations model stochastic movement of a molecular motor at a single intersection of protein filaments using the measurement data obtained through in vitro experiments (using kinesins and microtubules) conducted by the authors of this paper and evaluates the stochastic delivery of molecules from the senders to the receivers over multiple intersections of protein filaments arranged in an array topology. Simulation results show that molecular motors stochastically deliver cargo molecules to a specific receiver (or to a specific set of receivers) with a given probability over an array of protein filament intersections.

The ability to design systems of nanomachines may lead to new techniques for future applications. Systems of nanomachines may provide novel mechanisms to interact with cells for medicine, to detect and process waste molecules for environmental applications, or to self-organize nanomachines to manufacture objects. A nanomachine may require information about other nanomachines, such as distance to the other nanomachines, to achieve some applications. Molecular communication is one suitable communication technique for communicating among autonomous nanomachines which are limited in size and capability. In this paper, we consider how a nanomachine can estimate distance information from signal characteristics of a molecular communication. One transceiver nanomachine, T, requests another transceiver nanomachine, R, to transmit a feedback signal. T then estimates distance between T and R from the signal. Several design choices are considered for distance measurement. For transmission, options include releasing a spike of molecules or gradually releasing molecules. For propagation, options include whether or not the environment contains repeaters between T and R. For receiving, options include detecting a threshold concentration of molecules by sampling at a time instant or by capturing molecules over time. The options are compared in terms of range, delay, and accuracy through simulation.

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.

Nanomechatronics is a new emerging field at the intersection of nanotechnology and mechatronics. In this paper, control methods for nanomechatronic systems with respect to signaling, structure, and functions are reviewed, where control techniques that have been applied to nanobiosystems are presented. As an important example of nanomechatronic systems, molecular motors are discussed in terms of informatics and biophysics, respectively. A computational biological study on signaling pathways for the control of molecular motors in neurons is given to demonstrate a controller structure for nanomechatronics. As an extreme control method for living cells, a genome-level synthetic biotechnology is summarized. On the perspective of nanomechatronics, key factors of moleware robotics are examined toward the innovation of new nanorobots, which is one of the most promising applications of nanomechatronics in the new millennium.

The emerging interdisciplinary area of biologically inspired network systems research is reviewed. Examples of such systems found in the literature are grouped into two classes: in silico and in vitro/vivo network systems. For each class, background knowledge is provided concerning the biological systems, mechanisms, or materials used, and the manner in which they are applied to the design of the network systems is reviewed. Conclusions are drawn with the aim of providing future challenges for each class of biologically inspired network systems.

There is currently much debate in defining what form the future Internet will take. The current Internet is struggling to meet the needs of an ever-evolving society. This is largely due to the Internet now become a thriving marketplace with services at the core. The range, number and complexity of services are set to increase with an even more dynamic service environment envisioned in the future. However, as these services grow, service composition will become an important feature of the service environment, leading to new challenges in service discovery and composition mechanisms. At the same time, dynamic service environments will also require that the underlying infrastructure networks are flexible enough to handle the changing service landscape. One area this is particularly important is in dynamic routing to deal with highly dynamic and frequent service changes. In this paper, we adopt mechanisms from biology and apply these to the problems identified, resulting in an integrated bio-inspired service management and dynamic routing solution for Future Internet. We demonstrate how the bio-inspired mechanisms not only improve each problem individually, but through their integration also improve overall network performance. Simulation results are presented to validate the proposed solution.

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.

This paper proposes a novel framework for developing adaptive and scalable network services. In the proposed framework, a network service is implemented as a group of autonomous agents that interact in the network environment. Agents in the proposed framework are autonomous and capable of simple behaviors (e.g., replication, migration, and death). In this paper, an evolutionary adaptation mechanism is designed using genetic algorithms (GAs) for agents to evolve their behaviors and improve their fitness values (e.g., response time to a service request) to the environment. The proposed framework is evaluated through simulations, and the simulation results demonstrate the ability of autonomous agents to adapt to the network environment. The proposed framework may be suitable for disseminating network services in dynamic and large-scale networks where a large number of data and services need to be replicated, moved, and deleted in a decentralized manner.

This article presents a Web content adaptation and delivery mechanism based on application-level quality of service (QoS) policies. To realize effective Web content delivery for users, two kinds of application-level QoS policies, transmission time and transmission order of inline objects, are introduced. Next, we define a language to specify these policies. We show that transmission order control can be implemented using HTTP/1.1 pipelined requests in which a client recognizes the transmission order description in a Web page and simulates parallel transmission of inline objects by HTTP/1.1 range requests. Experimental results show that our proposed mechanism realizes effective content delivery to a diverse group of Internet users. Finally, we introduce two methods to specify application-level QoS policies, one by content authors, and the other by end users.