Internet Of Bio-Nano Things Research Articles

A Robust and Secure Drug Delivery With Single Transmitter and Dual Symmetrical Receivers in an Internet of Bio-Nano Things

A Robust and Secure Drug Delivery With Single Transmitter and Dual Symmetrical Receivers in an Internet of Bio-Nano Things

Energy Allocation for Multiuser Cooperative Molecular Communication Systems in Internet of Bio-Nano Things

Energy Allocation for Multiuser Cooperative Molecular Communication Systems in Internet of Bio-Nano Things

Joint Clock Offset and Skew Estimation Based on Correlated Propagation Delays in Internet of Bio-Nano Things

Joint Clock Offset and Skew Estimation Based on Correlated Propagation Delays in Internet of Bio-Nano Things

Hybrid Deep Learning Techniques for Securing Bioluminescent Interfaces in Internet of Bio Nano Things.

The Internet of bio-nano things (IoBNT) is an emerging paradigm employing nanoscale (~1-100 nm) biological transceivers to collect in vivo signaling information from the human body and communicate it to healthcare providers over the Internet. Bio-nano-things (BNT) offer external actuation of in-body molecular communication (MC) for targeted drug delivery to otherwise inaccessible parts of the human tissue. BNTs are inter-connected using chemical diffusion channels, forming an in vivo bio-nano network, connected to an external ex vivo environment such as the Internet using bio-cyber interfaces. Bio-luminescent bio-cyber interfacing (BBI) has proven to be promising in realizing IoBNT systems due to their non-obtrusive and low-cost implementation. BBI security, however, is a key concern during practical implementation since Internet connectivity exposes the interfaces to external threat vectors, and accurate classification of anomalous BBI traffic patterns is required to offer mitigation. However, parameter complexity and underlying intricate correlations among BBI traffic characteristics limit the use of existing machine-learning (ML) based anomaly detection methods typically requiring hand-crafted feature designing. To this end, the present work investigates the employment of deep learning (DL) algorithms allowing dynamic and scalable feature engineering to discriminate between normal and anomalous BBI traffic. During extensive validation using singular and multi-dimensional models on the generated dataset, our hybrid convolutional and recurrent ensemble (CNN + LSTM) reported an accuracy of approximately ~93.51% over other deep and shallow structures. Furthermore, employing a hybrid DL network allowed automated extraction of normal as well as temporal features in BBI data, eliminating manual selection and crafting of input features for accurate prediction. Finally, we recommend deployment primitives of the extracted optimal classifier in conventional intrusion detection systems as well as evolving non-Von Neumann architectures for real-time anomaly detection.

A frequency domain multiplexing scheme based on kernel density estimation for neural communication systems

Transmitting information in engineered neural communication systems is a promising solution to delay-sensitive applications for the Internet of Bio-Nanothings (IoBNTs). As widely used in wired and wireless communication systems, introducing multiplexing into neural communication system could improve channel transmission efficiency. In this paper, we model a neural communication system for IoBNTs and propose a neural signal multiplexing scheme for this system, based on frequency-division multiplexing (FDM) principles. The whole system including channel modeling, neural encoding, demultiplexing scheme, and decoding method using kernel density estimation (KDE) are presented. The optimal parameters for KDE and bit error probability are analyzed, and the performance of the proposed strategy is evaluated in terms of error rate and mutual information rate. The work can help researchers better understanding the underlying mechanism of neural multiplexing and pave the way for the implementation of IoBNT applications.

Graphene and related materials for the Internet of Bio-Nano Things

The Internet of Bio-Nano Things (IoBNT) is a transformative communication framework characterized by heterogeneous networks comprising both biological entities and artificial micro/nano-scale devices, so-called Bio-Nano Things (BNTs), interfaced with conventional communication networks for enabling innovative biomedical and environmental applications. Realizing the potential of IoBNT requires the development of new and unconventional communication technologies, such as molecular communications, as well as the corresponding transceivers, bio-cyber interfacing technologies connecting the biochemical domain of IoBNT to the electromagnetic domain of conventional networks, and miniaturized energy harvesting and storage components for the continuous power supply to BNTs. Graphene and related materials (GRMs) exhibit exceptional electrical, optical, biochemical, and mechanical properties, rendering them ideal candidates for addressing the challenges posed by IoBNT. This perspective article highlights recent advancements in GRM-based device technologies that are promising for implementing the core components of IoBNT. By identifying the unique opportunities afforded by GRMs and aligning them with the practical challenges associated with IoBNT, particularly in the materials domain, our aim is to accelerate the transition of envisaged IoBNT applications from theoretical concepts to practical implementations while also uncovering new application areas for GRMs.

A Role for Bottom-Up Synthetic Cells in the Internet of Bio-Nano Things?

The potential role of bottom-up Synthetic Cells (SCs) in the Internet of Bio-Nano Things (IoBNT) is discussed. In particular, this perspective paper focuses on the growing interest in networks of biological and/or artificial objects at the micro- and nanoscale (cells and subcellular parts, microelectrodes, microvessels, etc.), whereby communication takes place in an unconventional manner, i.e., via chemical signaling. The resulting "molecular communication" (MC) scenario paves the way to the development of innovative technologies that have the potential to impact biotechnology, nanomedicine, and related fields. The scenario that relies on the interconnection of natural and artificial entities is briefly introduced, highlighting how Synthetic Biology (SB) plays a central role. SB allows the construction of various types of SCs that can be designed, tailored, and programmed according to specific predefined requirements. In particular, "bottom-up" SCs are briefly described by commenting on the principles of their design and fabrication and their features (in particular, the capacity to exchange chemicals with other SCs or with natural biological cells). Although bottom-up SCs still have low complexity and thus basic functionalities, here, we introduce their potential role in the IoBNT. This perspective paper aims to stimulate interest in and discussion on the presented topics. The article also includes commentaries on MC, semantic information, minimal cognition, wetware neuromorphic engineering, and chemical social robotics, with the specific potential they can bring to the IoBNT.

A Survey for Possible Technologies of Micro/Nanomachines Used for Molecular Communication Within 6G Application Scenarios

The Internet of bio-nanothings (IoBNT) is one of the potential application scenarios in the 6th generation (6G) mobile network, which envisions the interaction between biological cells or nanodevices and the Internet. Molecular communication (MC) may offer an appropriate communication method for the nanodevices using chemical molecules as the information carriers. However, due to the complexity of experiments and insufficient interdisciplinary cooperation, MC study mainly focuses on theoretical research, which seriously hinders the MC’s advancement and further applications. Therefore, it is crucial to explore methods for constructing transmitter and receiver nanomachines to realize practical MC systems. Based on the research progress of micro/nanomachines (MNMs) in recent years, this paper summarizes the possible technologies for implementing MNMs used for MC systems within 6G application scenarios.

The Internet of bio-nano things in blood vessels: System design and prototypes

In this paper, we investigate the Internet of bionano things (IoBNT) which pertains to networks formed by molecular communications. By providing a means of communication through the ubiquitously connected blood vessels (arteries, veins, and capillaries), molecular communication-based IoBNT enables a host of new eHealth applications. For example, an organ monitoring sensor can transfer internal body signals through the IoBNT to health-monitoring applications. We empirically show that blood vessel channels introduce a new set of challenges in the design of molecular communication systems in comparison to free-space channels. Then, we propose cylindrical duct channel models and discuss the corresponding system designs conforming to the channel characteristics. Furthermore, based on prototype implementations, we confirm that molecular communication techniques can be utilized for composing the IoBNT. We believe that the promising results presented in this work, together with the rich research challenges that lie ahead, are strong indicators that IoBNT with molecular communications can drive novel applications for emerging eHealth systems.

Estimation and Detection for Molecular MIMO Communications in the Internet of Bio-Nano Things

For the Internet of Bio-Nano Things (IoBNT) applications demanding high transmission rates, a well-modeled Molecular Communication (MC) channel is essential. The existing studies proposing multiple-input and multiple-output (MIMO) models for MC, however, often make the unrealistic assumption of using ideal receivers with perfect absorption. Hence, this paper proposes a molecular MIMO channel model with spherical transmitters and partially-absorbing ligand receptor-based receivers underpinned by four unique parameters. For the non-analytical nature of the MIMO channel, we use a supervised learning algorithm to estimate the number of molecules in the reception space. We evaluate the root mean square error (RMSE) of our solution, which returns consistent results. The estimation is used for ligand-receptor binding statistics, in which the intersymbol inference (ISI) and molecular interference are considered. We also propose two techniques based on convolutional and recurrent neural networks (CNN & RNN) as alternatives to the generic threshold-based detection. Our detectors outperform the threshold-based technique; specifically, the CNN-based method improves the mean bit error rate (BER) performance three times.

Internet of Bio Nano Things-based FRET nanocommunications for eHealth.

The integration of the Internet of Bio Nano Things (IoBNT) with artificial intelligence (AI) and molecular communications technology is now required to achieve eHealth, specifically in the targeted drug delivery system (TDDS). In this work, we investigate an analytical framework for IoBNT with Forster resonance energy transfer (FRET) nanocommunication to enable intelligent bio nano thing (BNT) machine to accurately deliver therapeutic drug to the diseased cells. The FRET nanocommunication is accomplished by using the well-known pair of fluorescent proteins, EYFP and ECFP. Furthermore, the proposed IoBNT monitors drug transmission by using the quenching process in order to reduce side effects in healthy cells. We investigate the IoBNT framework by driving diffusional rate models in the presence of a quenching process. We evaluate the performance of the proposed framework in terms of the energy transfer efficiency, diffusion-controlled rate and drug loss rate. According to the simulation results, the proposed IoBNT with the intelligent bio nano thing for monitoring the quenching process can significantly achieve high energy transfer efficiency and low drug delivery loss rate, i.e., accurately delivering the desired therapeutic drugs to the diseased cell.

Intrabody Molecular Communication via Blood-Tissue Barrier for Internet of Bio-Nano Things

Molecular communication (MC) is an emerging communication paradigm that allows bio-nanomachines (NMs) to communicate using biochemical molecules as information carriers. It can be used in many promising biomedical applications such as the Internet of Bio-Nano Things (IoBNT) for targeted drug delivery and healthcare applications. In particular, the blood-tissue barrier (BTB) inside the body forms the main communication pathway for molecular information exchange between the NMs as well as between the intrabody nanonetwork and the bio-cyber interface in the IoBNT network. However, overcoming this barrier by the molecules is one of the main challenges for MC in the body. Therefore, spatiotemporal modeling of MC across the BTB is of particular interest. In this article, we develop a mathematical model and stochastic particle-based simulator for MC over high spatiotemporal resolution between mobile NMs in the blood capillary and the surrounding tissue. The transmitting bio-NM is modeled as a moving sphere with a continuous emission pattern over a specific duration. In this work, the blood capillary characteristics, including the BTB and blood flow, are modeled and their effect is examined on the molecular received signal. In addition, we examined the impact of the emission duration, the elimination rate, and the separation distance on the molecular received signal. The numerical results are verified using the developed particle-based simulator. This work can help in the optimum design and development of the IoBNT systems based on MC for biomedical applications, such as smart drug delivery and health monitoring systems.

Enhanced Modulation for Multiuser Molecular Communication in Internet of Nano Things

The novel concept of Internet of Nano Things (IoNT) brings even larger groups of nanomachines collaborating to achieve more complex tasks in the military, medical, and security fields. Moreover, Internet of Bio-Nano Things (IoBNT) is an emerging technology defining the seamless connection of nanomachines and biological entities with each other where they can access the traditional wireless communication networks to provide novel Internet of Things (IoT) applications, such as health monitoring, healthcare, and targeted therapy. The exchange of information between biological cells is based on the synthesis, transformation, emission, propagation, and reception of molecules. This information exchange is recently classified in telecommunications as molecular communication which is a biologically inspired technique to communicate in very small dimension networks. In nanonetworks, a high number of nanothings will operate in the same medium and they interfere with each other. Multiuser interference will create significant limits. Hence, we introduce to use the direction of releasing molecules as a new property to convey information. Releasing the molecules to the specific directions enhances the performance of molecular communication systems due to multiusers interference mitigation. Hence, adjacent transmitters can convey information in different directions, simultaneously. Then, we propose the binary direction shift keying (BDSK) modulation scheme where the transmitter pumps molecules in two different directions. Next, we obtain the error probability and achievable bit rate of BDSK modulation. Finally, we evaluate the performance of BDSK modulation by numerical results. The result of this article can be useful for molecular communication relay systems where relay nodes convey information to the different destinations.

Embedded Coded Relay System for Molecular Communications

With the emergence of the COVID-19 pandemic, the World Health Organization (WHO) has urged scientists and industrialists to explore modern information and communication technology (ICT) as a means to reduce or even eliminate it. The World Health Organization recently reported that the virus may infect the organism through any organ in the living body, such as the respiratory, the immunity, the nervous, the digestive, or the cardiovascular system. Targeting the abovementioned goal, we envision an implanted nanosystem embedded in the intra living-body network. The main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system (i.e., delivery of the therapeutic drug to the diseased tissue or targeted cell). The communication among the nanomachines is accomplished via communication-based molecular diffusion. The control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things (IoBNT). The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward (DF) principle to ensure reliable drug delivery to the targeted cell. Notably, both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into account. In this paper, a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate (BER) performance and high signal-to-noise ratio (SNR), while the detection process is based on maximum likelihood (ML) probability and minimum error probability (MEP). The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position, number of released molecules, relay and receiver size. Analysis results are validated through simulation and demonstrate that the proposed scheme can significantly improve delivery performance of the desirable drugs in the molecular communication system.

Low-Complexity Channel Codes for Reliable Molecular Communication via Diffusion.

It is envisioned that healthcare systems of the future will be revolutionized with the development and integration of body-centric networks into future generations of communication systems, giving rise to the so-called “Internet of Bio-nano things”. Molecular communications (MC) emerge as the most promising way of transmitting information for in-body communications. One of the biggest challenges is how to minimize the effects of environmental noise and reduce the inter-symbol interference (ISI) which in an MC via diffusion scenario can be very high. To address this problem, channel coding is one of the most promising techniques. In this paper, we study the effects of different channel codes integrated into MC systems. We provide a study of Tomlinson, Cercas, Hughes (TCH) codes as a new attractive approach for the MC environment due to the codeword properties which enable simplified detection. Simulation results show that TCH codes are more effective for these scenarios when compared to other existing alternatives, without introducing too much complexity or processing power into the system. Furthermore, an experimental proof-of-concept macroscale test bed is described, which uses pH as the information carrier, and which demonstrates that the proposed TCH codes can improve the reliability in this type of communication channel.

Internet of Bio-Nano Things: A review of applications, enabling technologies and key challenges

Internet of Bio-Nano Things (IoBNT) is envisioned to be a heterogeneous network of nanoscale and biological devices, so called Bio-Nano Things (BNTs), communicating via non-conventional means, e.g., molecular communications (MC), in non-conventional environments, e.g., inside human body. The main objective of this emerging networking framework is to enable direct and seamless interaction with biological systems for accurate sensing and control of their dynamics in real time. This close interaction between bio and cyber domains with unprecedentedly high spatio-temporal resolution is expected to open up vast opportunities to devise novel applications, especially in healthcare area, such as intrabody continuous health monitoring. There are, however, substantial challenges to be overcome if the enormous potential of the IoBNT is to be realized. These range from developing feasible nanocommunication and energy harvesting techniques for BNTs to handling the big data generated by IoBNT. In this survey, we attempt to provide a comprehensive overview of the IoBNT framework along with its main components and applications. An investigation of key technological challenges is presented together with a detailed review of the state-of-the-art approaches and a discussion of future research directions.

Securing Bio-Cyber Interface for the Internet of Bio-Nano Things using Particle Swarm Optimization and Artificial Neural Networks based parameter profiling.

Internet of bio-nano things (IoBNT) is a novel communication paradigm where tiny, biocompatible and non-intrusive devices collect and sense biological signals from the environment and send them to data centers for processing through the internet. The concept of the IoBNT has stemmed from the combination of synthetic biology and nanotechnology tools which enable the fabrication of biological computing devices called Bio-nano things. Bio-nano things are nanoscale (1-100nm) devices that are ideal for in vivo applications, where non-intrusive devices can reach hard-to-access areas of the human body (such as deep inside the tissue) to collect biological information. Bio-nano things work collaboratively in the form of a network called nanonetwork. The interconnection of the biological world and the cyber world of the Internet is made possible by a powerful hybrid device called Bio Cyber Interface. Bio Cyber Interface translates biochemical signals from in-body nanonetworks into electromagnetic signals and vice versa. Bio Cyber Interface can be designed using several technologies. In this paper, we have selected bio field-effect transistor (BioFET) technology, due to its characteristics of being fast, low-cost, and simple The main concern in this work is the security of IoBNT, which must be the preliminary requirement, especially for healthcare applications of IoBNT. Once the human body is accessible through the Internet, there is always a chance that it will be done with malicious intent. To address the issue of security in IoBNT, we propose a framework that utilizes Particle Swarm Optimization (PSO) algorithm to optimize Artificial Neural Networks (ANN) and to detect anomalous activities in the IoBNT transmission. Our proposed PSO-based ANN model was tested for the simulated dataset of BioFET based Bio Cyber Interface communication features. The results show an improved accuracy of 98.9% when compared with Adam based optimization function.

MIMO Operations in Molecular Communications: Theory, Prototypes, and Open Challenges

The Internet of Bio-nano Things is a significant development for next generation communication technologies. Because conventional wireless communication technologies face challenges in realizing new applications (e.g., in-body area networks for health monitoring) and necessitate the substitution of information carriers, researchers have shifted their interest to molecular communications (MC). Although remarkable progress has been made in this field over the last decade, advances have been far from acceptable for the achievement of its application objectives. A crucial problem of MC is the low data rate and high error rate inherent in particle dynamics specifications, in contrast to wave-based conventional communications. Therefore, it is important to investigate the resources by which MC can obtain additional information paths and provide strategies to exploit these resources. This study aims to examine techniques involving resource aggregation and exploitation to provide prospective directions for future progress in MC. In particular, we focus on state-of-the-art studies on multiple-input multiple-output (MIMO) systems. We discuss the possible advantages of applying MIMO to various MC system models. Furthermore, we survey various studies that aimed to achieve MIMO gains for the respective models, from theoretical background to prototypes. Finally, we conclude this study by summarizing the challenges that need to be addressed.

Rate control for therapeutic applications in Internet of Bio-Nano Things using molecular communication: A survey

Molecular communication is transmitting and receiving chemical signals using molecules and is an interdisciplinary field between nanotechnology, biology, and communication. Molecular communication can be used for connecting bio-nano things. The connected nano-things build a nano-network. Transport mechanisms in molecular communication include free diffusion, gap junction channels, molecular motors, self-propelling microorganisms like bacteria and random collision of mobile nano-things. Free diffusion is the most widely used transport mechanism in the literature. Brownian motion is always available and its energy consumption is zero. This paper explores the therapeutic applications of rate control in the Internet of Bio-Nano Things and reviews the recent trends and advancements in the field of molecular communication. These methods aim to guarantee the desired rate of drug molecules at the target site and overcome the side effects of excessive emission.

Transmission and detection techniques for Internet of Bio-Nano Things applications with static and mobile molecular communication: A survey

Recent studies have shown that designing communication systems at nanoscale and microscale for the Internet of Bio-Nano Things (IoBNT) applications is possible using Molecular Communication (MC), where two or multiple nodes communicate with each other by transmitting chemical molecules. The basic steps involved in MC are the transmission of molecules, propagation of molecules in the medium, and reception of the molecules at the receiver. Various transmission schemes, channel models, and detection techniques have been proposed for MC in recent years. This paper, therefore, presents an exhaustive review of the existing literature on detection techniques along with their transmission schemes under various MC setups. More specifically, for each setup, this survey includes the transmission and detection techniques under four different environments to support various IoBNT applications: (i) static transmitter and receiver in a pure-diffusive channel, (ii) static transmitter and receiver in a flow-induced diffusive channel, (iii) mobile transmitter and receiver in a pure-diffusive channel, (iv) mobile transmitter and receiver in a flow-induced diffusive channel. Also, performances and complexities of various detection schemes have been compared. Further, several challenges in detection and their possible solutions have been discussed under both static and mobile scenarios. Furthermore, some experimental works in MC are presented to show realistic transmission and detection procedures available in practice. Finally, future research directions and challenges in the practical design of the transmitter and receiver are described to realize MC for IoBNT health applications.