Michael Taynnan Barros

Transmission Protocols for Calcium-Signaling-Based Molecular Communications in Deformable Cellular Tissue

Molecular communications is a new paradigm that enables nanomachines to communicate within a biological environment. One form of molecular communications is calcium (Ca2+) signaling, which occurs naturally in living biological cells. Ca2+ signaling enables cells in a tightly packed tissue structure to communicate at short ranges with neighboring cells. The achievable mutual information of Caa2+ signaling between tissue embedded nanomachines is investigated in this paper, focusing in particular on the impact that the deformation of the tissue structure has on the communication channel. Based on this analysis, a number of transmission protocols are proposed; nanomachines can utilize these to communicate using Ca2+ signaling. These protocols are static time-slot configuration, dynamic time-slot configuration, dynamic time-slot configuration with silent communication, and improved dynamic time-slot configuration with silent communication (IDTC-SC). The results of a simulation study show that IDTC-SC provides the maximum data rate when tissues experience frequent deformation.

Using Information Metrics and Molecular Communication to Detect Cellular Tissue Deformation

Calcium-signaling-based molecular communication has been proposed as one form of communication for short range transmission between nanomachines. This form of communication is naturally found within cellular tissues, where Ca 2+ ions propagate and diffuse between cells. However, the naturally flexible structure of cells usually leads to the cells dynamically changing shape under strain. Since the interconnected cells form the tissue, a change in shape of one cell will change the shape of the neighboring cells and the tissue as a whole. This will in turn dramatically impair the communication channel between the nanomachines. We propose a process for nanomachines utilizing Ca 2+ based molecular communication to infer and detect the state of the tissue, which we term the Molecular Nanonetwork Inference Process. The process employs a threshold based classifier that identifies its threshold boundaries based on a training process. The inference/detection mechanism allows the destination nanomachine to determine: i) the type of tissue deformation; ii) the amount of tissue deformation; iii) the amount of Ca 2+ concentration emitted from the source nanomachine; and iv) its distance from the destination nanomachines. We evaluate the use of three information metrics: mutual information, mutual information with generalized entropy and information distance. Our analysis, which is conducted on two different topologies, finds that mutual information with generalized entropy provides the most accurate inferencing/detection process, enabling the classifier to obtain 80% of accuracy on average.

Routing Architecture for Vehicular Ad-Hoc Networks

The actual proposed routing protocols for VANETs (Vehicular Ad-hoc Networks) present different features for communication among hosts/vehicles considering the strong topology change, but most of these features are needed for routing in these specific networks. These routing protocols support vehicle traffic on a large scale, intense mobility of vehicles, connections without link breakage, etc. But as they are different protocols the routers (nodes) have to switch to a routing protocol in a certain moment, which is a problem. This paper presents a routing architecture for VANETs to face it. The most important technical features for routing in VANETs were grouped in the Routing Architecture. To validate the proposed architecture several existing protocols were unified in the architecture producing a new routing protocol for VANETs. The produced protocol is the Generic Vehicular Dynamic Source Routing (GVDSR). Simulations of the GVDSR protocol have been made on the Malaga city showing the contributions and advantages for routing performance. The proposed architecture and protocol were simulated in the Network Simulator 2 featuring better performance than the compared protocols.

Error control for calcium signaling based molecular communication

Calcium signaling is one of the most widely studied means of providing communication for molecular communications in nanonetworks. In this paper, we investigate error control approaches for calcium signaling based molecular communications. Taking an information theoretic approach we show, using a stochastic simulation model, how error conditions such as signal fading, multipath propagation and spatial noise can affect the communication reliability. In order to counter these issues, we proposed using baseband modulations techniques (Return-to-zero (RZ) and Non-return-to-zero (NRZ)) in combination with channel coding (Reed Solomon) to improve the performance of the communication system.

Comparative End-to-End Analysis of Ca 2+ -Signaling-Based Molecular Communication in Biological Tissues

Calcium (Ca2+)-signaling-based molecular communication is a short-range communication process that diffuses and propagates ions between the cells of a tissue. The communication process is initiated via stimulation and amplification of the production of Ca2+ ions within a cell; these ions then diffuse through a physical connection between cells called a gap junction. Ca2+ signaling can be found in different classes of cell. In excitable cells, initiation of the Ca2+-signaling process is accompanied by an electrical component; for nonexcitable cell types, the electrical component is absent; while hybrid cells exhibit both behaviors. This paper provides a comparison and analysis of the communication behavior in tissues comprised three specific cell types that utilize Ca2+ signaling: epithelium cells (nonexcitable), smooth muscle cells (excitable), and astrocytes (hybrid). The analysis focuses on spatiotemporal Ca2+ concentration dynamics and how they are influenced by the intracellular signaling process, the molecular diffusion delay, the gain and capacity of the communication channel, as well as intracellular signaling interference. This analysis of the communication behavior in the context of tissues provides insights useful for, inter alia, the design of nanomachines that are situated within tissues and that use analysis of the communication channel to infer tissue health.

Adaptive transmission protocol for molecular communications in cellular tissues

One form of molecular communications for short range transmission between nanomachines is Calcium Signaling. This form of signaling is commonly found in cellular tissues, which consist of tightly packed cells, whereby Ca2+ ions propagate and diffuse between the cells. However, the natural flexible structure of cells usually leads to them dynamically changing shapes under certain strains and forces. Since the interconnected cells form a tissue, changes in the shape of one cell will change the shape of neighboring cells and the tissue as a whole. This may in turn significantly impair the communication channel between the nanomachines (which we assume to be embedded within the cells). In order to counter this problem, we propose an adaptive transmission protocol for Ca2+ signaling based molecular communications in cellular tissues. The protocol operates in two phases. The first phase utilizes information metrics to infer the state of the tissue; second phase then involves the determination of the most appropriate time-slot for bit transmission. In this way, we aim to improve the information rate by using a time slot length that is appropriate for the prevailing type of tissue deformation. Through simulation studies we show that, for two types of deformation and two different topologies, our protocol can improve the information rate performance by 15%.

Ca 2+ -signaling-based molecular communication systems: Design and future research directions

Abstract Nanomedicine is revolutionizing current methods for diagnosing, treatment and prevention of diseases with the integration of molecular biology, biotechnology as well as nanotechnology for sensing and actuation capabilities at the molecular scale using nanoscale devices, namely nanomachines. While numerous examples of these applications have been tested in vivo , the real deployments are far from reality. Limitations in controlling, monitoring, miniaturization, and computing inhibit access and manipulation of information at the nano-scale. Integrating communication and networking functionalities provide new opportunities for such challenges with the newly introduced Molecular Communications. These natural communication systems are found with plurality inside the human body. The current challenge is to utilize these natural systems to create artificial biocompatible communication networks that can interconnect multiple nanomachines in multiple parts of the body and connected to the cloud, is defined as the Internet of Bio-Nano Things ( IoBNT ). Nanonetworks inside cellular tissues perform communication using a signaling process such as Ca 2+ . This specifically signaling process is very important for many regulatory functions in tissues and its control and communication is crucial to allow nanomedicine capabilities towards diagnosis and treatments of diseases at the nano-scale. This paper presents a review of techniques that enable the design of the Ca 2+ -signaling-based molecular communication system for cellular tissues, essential tools for its deployment, application and, lastly, the research future direction in this field. In the end, one must acquire the sufficient knowledge to understand both biological and telecommunication concepts that encompass this technology to bring it further.

Integrated Terahertz Communication With Reflectors for 5G Small-Cell Networks

As the cellular networks continue to progress between generations, the expectations of 5G systems are planned toward high-capacity communication links that can provide users access to numerous types of applications (e.g., augmented reality and holographic multimedia streaming). The demand for higher bandwidth has led the research community to investigate unexplored frequency spectrums, such as the terahertz band for 5G. However, this particular spectrum is strived with numerous challenges, which includes the need for line-of-sight (LoS) links as reflections will deflect the waves as well as molecular absorption that can affect the signal strength. This is further amplified when a high quality of service has to be maintained over infrastructure that supports mobility, as users (or groups of users) migrate between locations, requiring frequent handover for roaming. In this paper, the concept of mirror-assisted wireless coverage is introduced, where smart antennas are utilized with dielectric mirrors that act as reflectors for the terahertz waves. The objective is to utilize information such as the users location and to direct the reflective beam toward the highest concentration of users. A multiray model is presented in order to develop the propagation models for both indoor and outdoor scenarios in order to validate the proposed use of the reflectors. An office and a pedestrian-walking scenarios are used for indoor and outdoor scenarios, respectively. The results from the simulation work show an improvement with the usage of mirror-assisted wireless coverage, improving the overall capacity, the received power, the path loss, and the probability of LoS.

IP traffic classifiers applied to DiffServ networks

The future Internet scenario consists of a higher number of users and applications, which demand more resources from the communication infrastructure. Techniques for providing performance and scalability, such as Traffic Engineering (TE), will always be necessary even if the transmission rate is very high, because of such demands. Quality of Service is one of the solutions that can be used to improve the traffic engineering in the Internet, with the most referenced architecture: DiffServ. In general, TE needs traffic classification to accurately identify the input traffic and manage it properly. However, the current DiffServ port traffic classifier is considered outdated. This paper presents a performance evaluation of machine learning traffic classification solutions applied to DiffServ, and investigates their benefits on network performance. For a backbone network with 40 nodes, the performance of the network can increase up to 15% for both data and voice traffic.

Performance of wavelength assignment heuristics in a dynamic optical network with adaptive routing and traffic grooming

This paper present the performance analysis of the wavelength assignment four heuristics First-Fit, Random, Least-Used and Most-Used, considering adaptive routing and traffic grooming capabilities in the network. The goal of this comparison is to verify if some of those algorithms present a better performance with relation to First-Fit, considering these capabilities.