Modeling, methodologies and tools for molecular and nano-scale communications : modeling, methodologies and tools

This volume reports on cutting-edge modeling techniques, methodologies and tools used to understand, design and engineer nanoscale communication systems, such as molecular communication systems. Moreover, it includes introductory materials for those who are new to the field. The book's interdis...

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Bibliographic Details
Main Authors Suzuki, Junichi, Nakano, Tadashi, Moore, Michael John
Format eBook Book
LanguageEnglish
Published Cham Springer 2017
Springer International Publishing AG
Springer International Publishing
Edition1
SeriesModeling and Optimization in Science and Technologies
Subjects
Biomedical engineering
Biomedical Engineering/Biotechnology
Computer Communication Networks
Engineering
Molecular communication (Telecommunication)
Multimedia communications
Nanotechnology
Nanotechnology and Microengineering
Optical and Electronic Materials
Online AccessGet full text
ISBN3319506862
9783319506869
ISSN2196-7326
2196-7334
DOI10.1007/978-3-319-50688-3

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Table of Contents:
  • 2.3 Computational Analysis of Signaling Pathway Networks in Terms of Communication Networks -- 3 Conclusion -- References -- 12 Quantifying Robustness in Biological Networks Using NS-2 -- 1 Computational Modelling -- 2 Mapping GRNs to WSNs -- 3 NS-2 Simulation Setup -- 3.1 Network Generation -- 3.2 Sink Selection Strategy -- 3.3 SVM Validation -- 3.4 Contributions of Topological Metrics to GRN Robustness -- 4 Case Study: Comparison of Derived Networks from E. Coli and Yeast -- 5 Challenges and Future Directions -- References -- Electromagnetic-Based Nano-scale Communication -- 13 Fundamentals of Graphene-Enabled Wireless On-Chip Networking -- 1 Introduction -- 2 Open Issues in Communication Within Manycore Chip Multiprocessors -- 3 Graphene-Enabled Wireless Network-on-Chip -- 3.1 Modeling GWNoC Communications -- 3.2 Design Decisions for GWNoC Protocols -- 4 Conclusions and Future Work -- References -- 14 Energy Harvesting in Nanonetworks -- 1 Introduction -- 2 Energy Harvesting -- 2.1 Taxonomy of Energy Harvesting -- 2.2 Sources of Energy for Nanonodes -- 2.3 Future -- 3 Communication -- 3.1 Electromagnetic Communication -- 3.2 Pulse-Based Communication Model for Nanonetworks -- 4 Modeling of Energy Harvesting and Consumption -- 4.1 Models for Other Networks -- 4.2 Model for Nanonetworks -- 4.3 Summary -- 5 Optimizing Energy Consumption Factors -- 5.1 Optimization Model -- 5.2 Simulation -- 5.3 Scenario 1 (G=1, α=0.1, Repetition=1) -- 5.4 Scenario 2 (G=4, α= 0.1, Repetition=5) -- 6 Open Issues and Challenges -- 6.1 Optimization of Energy Consumption -- 6.2 Energy Harvesting-Aware Protocols -- 7 Summary -- References -- 15 Nanoscale Communications Based on Fluorescence Resonance Energy Transfer (FRET) -- 1 Introduction -- 2 Theory of FRET -- 3 FRET-Based Point-to-Point Nanoscale Communication Channel with Single Exciton Transmission
  • 6 Discussion of Simultion Study for Communication Principles in Simulators -- 6.1 Available Simulators -- 6.1.1 Molecular Motor Based Simulator [24] -- 6.1.2 3D Brownian Motion Simulator [25] -- 6.1.3 N3 Sim [26] -- 6.1.4 Simulator Based on Java [27] -- 6.1.5 NanoNS [28] -- 6.2 Cell Tool Kit Sim -- 7 Conclusion -- References -- Molecular Communication in Biology -- 9 On Regulation of Neuro-spike Communication for Healthy Brain -- 1 Introduction -- 2 Neuronal Communication at Cellular Level -- 2.1 Calcium in Neuronal Communications -- 2.2 Electromagnetic Exposure on Neuronal Systems -- 2.3 Possible Mechanisms Behind Neuronal Effects in Response to EMR and MF -- 3 Neuron's Message Transmission -- 3.1 Fundamental Neuronal Operating Principles -- 3.2 Synaptic Transmission -- 4 Neuro-Spike Communications at Network Level -- 4.1 Graph Theoretical Modeling of Neuronal Connectivity -- 4.2 Memory Networks -- 5 ICT-Inspired Treatment of Neurodegenerative Diseases -- 5.1 Complementary Techniques of Calcium Controlling -- 5.2 Graph-Based Strategies of Diagnosis and Treatment of Neuronal Disorders -- 6 Chapter Summary -- References -- 10 Molecular Dynamics Simulations of Biocorona Formation -- Abstract -- 1 Biomolecule-Nanoparticle Interactions -- 2 Biomolecular MD Simulations Overview -- 3 MD Simulations of Protein-Nanoparticle Interactions -- 4 GPU-Optimized MD Simulations -- 5 GPU-Optimized MD Simulations of Biocorona Formation -- 6 Conclusions -- Acknowledgements -- References -- 11 Modeling Cell Communication by Communication Engineering -- Abstract -- 1 Introduction -- 2 Informatics Principles of Cell Communication: Complex Network of Cellular Signaling Pathways -- 2.1 Discrete State Transition of Cell Communication in Terms of Complex Systems -- 2.2 An Example of the Complex Mechanism of Cell Signaling
  • 2.2 Emission and Reception Processes -- 3 Modulation Techniques for MCvD -- 3.1 Amplitude-Based Modulations -- 3.2 Molecule Type-Based Modulations -- 3.3 Frequency-Based Modulations -- 3.4 Timing-Based Modulation -- 3.5 Realization with Isomers -- 4 Research Challenges -- 5 Conclusions -- References -- 6 The Use of Coding and Protocols Within Molecular Communication Systems -- Abstract -- 1 Introduction -- 2 Analysis of the Diffusive Medium -- 3 Communication Channel Model -- 4 Error Correction Coding -- 5 SW-ARQ Schemes Within the Nano-Scale -- 6 Summary -- References -- 7 Understanding Communication via Diffusion: Simulation Design and Intricacies -- 1 Introduction -- 2 Simulation Design of CvD -- 2.1 Simulation of Brownian Motion -- 3 Simulation of Complex CvD Systems -- 3.1 Transmission and Reception Enhancements -- 3.2 Distributed Simulations -- 4 Conclusions -- References -- 8 An Architecture of Calcium Signaling for Molecular Communication Based Nano Network -- 1 Introduction -- 2 Overview of Nanonetworks Comprising of Nanomachine (Node) -- 2.1 Electromagnetic Communication -- 2.2 Molecular Communication -- 3 Communication Among Nano-Machines -- 3.1 Molecular Communication -- 3.1.1 Molecular Communication Using Molecular Motors -- 3.1.2 Molecular Communication Using Calcium Signaling -- 3.1.3 Molecular Communication Using Pheromones -- 3.1.4 Molecular Neuro-Spike Communication -- 3.2 Nano-Electromagnetic Communication -- 4 Advantages of Molecular Communication Over Electromagnetic Communication in Nano-Networks -- 5 Proposed Architecture for Nanonetwork Using Molecular Communication with Calcium Signaling -- 5.1 Protocol Stack Components in Physical Channel Layer -- 5.2 Detail Discussion on Protocol Stack Components -- 5.3 Channel Modeling and Solution Scheme -- 5.4 Evaluation and Observations
  • 4 Fick's Laws Diffusion Dynamics -- 4.1 Fick's Laws Concentration Channel -- 4.2 Pulse-Transmitted Scheme -- 4.2.1 Single Pulse Transmission -- 4.2.2 Bit Sequence Transmission -- 4.2.3 Communication Range- and Rate-Dependent Characteristics -- 4.2.4 Multilevel PAM Scheme -- 4.2.5 Reduced Pulse-Width Scheme -- 4.2.6 Sinusoidal-Based Signaling -- 5 Signal Detection -- 5.1 Stochastic Concentration Channel: Signal and Noise Models -- 5.2 Sampling-Based Detection -- 5.3 Strength-Based Detection -- 6 Ligand-Receptor Binding -- 6.1 Reaction Rate Equations -- 6.2 Stochastic Chemical Kinetics -- 7 Conclusion -- Acknowledgements -- References -- 3 Physical Channel Model for Molecular Communications -- 1 Introduction -- 2 How Molecular Communication Works? -- 2.1 Encoding -- 2.2 Modulation -- 2.3 Transmission -- 2.4 Signal Propagation -- 2.5 Receiving and Decoding -- 2.6 Noise -- 2.7 Inter-symbol Interference (ISI) -- 2.8 Channel Memory -- 2.9 Delay -- 3 Molecular Communication Model -- 3.1 Passive Transport-Based Molecular Communication -- 3.2 Active Transport-Based Molecular Communication -- 3.3 Energy Model -- 4 Free Diffusion Molecular Communication Channel -- 4.1 Capacity Performance -- 4.2 Bit Error Rate (BER) Performance -- 5 Related Works -- 6 Conclusion -- References -- 4 Modulation in Molecular Communications: A Look on Methodologies -- 1 Introduction -- 2 Motivation for Modulation Research in Molecular Communications -- 3 Modulation in Molecular Communications -- 3.1 Concentration Based Modulation -- 3.2 Molecule Type Based Modulation -- 3.3 Release Time Based Modulation -- 3.4 Mixed Type Modulation -- 3.5 Modulation and Nanomachines in Molecular Communication -- 4 Conclusions -- References -- 5 Modulation Techniques for Molecular Communication via Diffusion -- 1 Introduction -- 2 Molecular Communication via Diffusion -- 2.1 Propagation Process
  • Intro -- Preface -- Contents -- Fundamentals of Molecular Communication -- 1 Concentration-Encoded Molecular Communication in Nanonetworks. Part 1: Fundamentals, Issues, and Challenges -- Abstract -- 1 Introduction -- 2 Nanomachines and Nanonetworks -- 2.1 Approaches to Development of Nanomachines -- 2.2 Expected Features and Functionalities of a Nanomachine -- 2.3 Architecture of a Nanomachine -- 2.4 Engineered Natural and Synthetic Nanomachines -- 3 Communication Between Nanomachines in a Nanonetwork -- 3.1 Communication at the Nanoscale -- 3.2 Dry and Wet Techniques -- 3.3 MC and CEMC -- 3.4 CEMC Phases -- 4 Diffusion-Based Propagation of Molecules -- 4.1 Macroscopic Theory of Diffusion in CEMC -- 4.2 Microscopic Theory of Diffusion in CEMC -- 4.3 Diffusion-Based Noise and Interference -- 5 CEMC Limitations -- 5.1 Speed of Communication -- 5.2 Communication Ranges -- 5.3 Noise and Interference -- 6 Research Issues and Challenges -- 6.1 Concentration Attenuation -- 6.2 Intersymbol Interference -- 6.3 Determination of Communication Ranges -- 6.4 Determination of Transmission Data Rates -- 6.5 Addressing Mechanisms -- 6.6 Efficient Signal Detection Schemes -- 6.7 Investigations into Channel Coding Schemes -- 6.8 System Model and Performance Evaluation -- 6.9 Testbed Development, Simulator, and Experimental Opportunities -- 7 Engineered CEMC -- 8 Applications of CEMC and Nanonetworks -- 9 Conclusion -- Acknowledgements -- References -- 2 Concentration-Encoded Molecular Communication in Nanonetworks. Part 2: Performance Evaluation -- Abstract -- 1 Introduction -- 2 System Model -- 2.1 System Components -- 2.2 CIR Characteristics: Distance and Temporal Dependence -- 3 Transmission and Modulation Schemes -- 3.1 Impulse Modulation -- 3.2 Pulse Amplitude Modulation -- 3.3 Multilevel Pulse Amplitude Modulation -- 3.4 Sinusoidal Transmission
  • 3.1 Channel Model