Nanonetworks: The Future of Communication and Computation

fmatter
	Title Page
	Copyright
	Contents
	List of Figures
	List of Tables
	About the Author
	Preface
	Acknowledgments
ch1
	1.1 Etymology
	1.2 Science Fiction
	1.3 Nanotechnology Intuition
	1.4 Example Applications
	1.5 Unique Problems and Challenges
	1.6 Summary
	1.7 Chapter Overview
ch2
	2.1 Philosophy
		2.1.1 Ancient India
		2.1.2 Greece
		2.1.3 Modern Era
		2.1.4 Since 2008
	2.2 Manufacturing Accuracy
		2.2.1 Antiquity
		2.2.2 Middle Ages
		2.2.3 Modernity
			2.2.3.1 Manufacturing Methods
			2.2.3.2 Microscopes and Imaging
		2.2.4 From 2D to 3D
		2.2.5 Placement Accuracy
	2.3 State of the Art
		2.3.1 Artificial Materials
		2.3.2 Programmable Matter
		2.3.3 Biology
		2.3.4 Hybrid
	2.4 Summary
ch3
	3.1 Nanotechnology in Materials and Industry
	3.2 Medicine
		3.2.1 Convenient Permanent Health Monitoring
		3.2.2 Targeted Drug Delivery
		3.2.3 Immediate (Local) Treatment
		3.2.4 Smart Medicine
		3.2.5 PCR Alternative
		3.2.6 Personalized Medicine
		3.2.7 Vaccines
		3.2.8 Immune Enhancement
	3.3 Military
	3.4 Agriculture and Geology
	3.5 Future Developments
	3.6 Summary
ch4
	4.1 Construction Paradigms
	4.2 Materials
		4.2.1 Inorganic Carbon
		4.2.2 Molecules
			4.2.2.1 Carbon‐Based Nanoclusters and Fullerenes
			4.2.2.2 Carbon Nanotubes
	4.3 Nanoparticles
		4.3.1 DNA
		4.3.2 Metamaterials and Metasurfaces
	4.4 Defining Complex Nanostructures
		4.4.1 Component‐based Approach
		4.4.2 Components
			4.4.2.1 Actuators A
			4.4.2.2 Communication C
			4.4.2.3 Information Processing I+
			4.4.2.4 Locomotion L
			4.4.2.5 Memory M
			4.4.2.6 Energy Supply E
			4.4.2.7 Sensors O
			4.4.2.8 Timer T
		4.4.3 Nanonetworks as Markov Decision Processes
			4.4.3.1 Markov Decision Processes
			4.4.3.2 Partially Observable MDPs
			4.4.3.3 DecPOMDP
			4.4.3.4 DecPOMDP with Communication
			4.4.3.5 Mapping DecPOMDPcom to Components
	4.5 Nature Adaptation
	4.6 Miniaturization
	4.7 Self‐assembly
		4.7.1 DNA Origami
		4.7.2 DNA Templating
		4.7.3 Polymerase Chain Reaction
		4.7.4 Tile‐based Self‐assembly
		4.7.5 From Wang to Holliday
			4.7.5.1 Abstract Tile‐assembly Model
			4.7.5.2 Kinetic Tile‐assembly Model
			4.7.5.3 Two‐handed Tile‐assembly Model
			4.7.5.4 Two‐handed Kinetic Tile‐assembly Model
	4.8 DNA Errors
	4.9 Error Correction Mechanisms
		4.9.1 k×k Proofreading
		4.9.2 Snaked Proofreading
		4.9.3 3D Snaked Proofreading
	4.10 State of the Art of Miniature Structures and Devices
		4.10.1 DNA Squares and DNA Boxes
			4.10.1.1 Naive 2D Algorithm
			4.10.1.2 Naive 3D Algorithm
			4.10.1.3 3D Linear Runtime Algorithm
			4.10.1.4 Constant Runtime Algorithm
			4.10.1.5 Pragmatic Logarithmic Runtime Algorithm
		4.10.2 DNA Origami Boxes
		4.10.3 Microbots
	4.11 Simulation
		4.11.1 ISU TAS
		4.11.2 Xgrow
		4.11.3 NetTAS
		4.11.4 caDNAno – DNA Origami Simulation
	4.12 Summary
ch5
	5.1 State at the Nanoscale
	5.2 Computation
	5.3 Complexity Theory
		5.3.1 Complexity at the Nanoscale
		5.3.2 Reductions
	5.4 Computational Analysis of Nanoscale Applications
		5.4.1 Extraction of Mathematical Problems
			5.4.1.1 Arithmetic and Logical Operators
			5.4.1.2 Communication
			5.4.1.3 Complex Operations
			5.4.1.4 Pattern Matching and Parity
			5.4.1.5 Security
		5.4.2 Classification in Complexity Classes
			5.4.2.1 Uncategorizable Problems
		5.4.3 Landau Notation
	5.5 Computational Models for the Nanoscale
		5.5.1 Nature‐Inspired vs. Artificial Models
		5.5.2 The Turing Machine
		5.5.3 Circuit‐Based Computers
		5.5.4 Artificial Neural Networks
		5.5.5 Quantum‐Dot Cellular Automata
		5.5.6 Chemical Reaction Networks
		5.5.7 Genetic Circuits
		5.5.8 Quantum Computing
	5.6 Self‐assembly Systems
		5.6.1 Truth Values in Self‐assembly Systems
		5.6.2 Message Molecules
		5.6.3 Ligands
		5.6.4 Message Molecule Receptors
		5.6.5 Medical Example Scenario
		5.6.6 Modularizing the Scenario
		5.6.7 Errors in Message Molecules
		5.6.8 Logical Combination of Message Molecules
		5.6.9 Modeling Message Molecules
			5.6.9.1 Solving The Decision Problem
			5.6.9.2 k‐Bit Or
			5.6.9.3 k‐Bit Thres
			5.6.9.4 k‐Bit Add
			5.6.9.5 k‐Bit Mult
			5.6.9.6 k‐Bit Xor
			5.6.9.7 k‐Bit‐Count
	5.7 Finding Programs for Nanodevices
		5.7.1 Solving DecPOMDPcoms
			5.7.1.1 Lifting
		5.7.2 Value Iteration
		5.7.3 Genetic/Evolutionary Algorithms
	5.8 Summary
ch6
	6.1 A Brief History of Communication
	6.2 Definitions
		6.2.1 Gateways
		6.2.2 Communication Parameter Overview
	6.3 Electromagnetic Communication
		6.3.1 History and Driving Forces
		6.3.2 5G and 6G
		6.3.3 Channel Models
		6.3.4 Information Representation
	6.4 Molecular Communication
		6.4.1 Classical Molecular Communication
		6.4.2 DNA
		6.4.3 Channel Models
	6.5 Acoustic Communication
		6.5.1 Nanoscale Acoustic Communication
		6.5.2 Medical Constraints
	6.6 Quantum Communication
	6.7 FRET
	6.8 Nanophotonics
	6.9 Comparison
	6.10 Multi‐hop Communication
		6.10.1 Addressing
		6.10.2 Routing Protocols
		6.10.3 Hop‐count Routing
	6.11 Communication and Network Simulators
	6.12 Summary
ch7
	7.1 Definition
	7.2 Passive Movement
		7.2.1 Brownian Motion
		7.2.2 Diffusion
		7.2.3 Blood Stream and Bulk Flow
	7.3 Active Movement
		7.3.1 Chemotaxis
		7.3.2 Other Motor Proteins
		7.3.3 Artificial Movement
		7.3.4 Comparison of Locomotion Types
	7.4 Localization
		7.4.1 Multi‐gateway Hop‐Count Localization
		7.4.2 Age of Information
		7.4.3 Tissue Fingerprinting
	7.5 Simulation
		7.5.1 BloodVoyagerS
		7.5.2 MEHLISSA
			7.5.2.1 Body Module
			7.5.2.2 Organ Module
			7.5.2.3 Capillary Module
			7.5.2.4 Cell Module
	7.6 Organs‐on‐Chips
	7.7 Summary
ch8
	8.1 Application Scenarios
	8.2 Measuring Systems
	8.3 Sensors
		8.3.1 CNT‐based Sensors
		8.3.2 Magnetic Sensors
		8.3.3 Molecule Counters and Biosensors
	8.4 Actuators
		8.4.1 Motors
		8.4.2 Antennas
		8.4.3 Medication
		8.4.4 Dispenser
		8.4.5 Switches
		8.4.6 Mechanical Actuators
	8.5 Summary
ch9
	9.1 Energy Sources
	9.2 Storing Energy
		9.2.1 Batteries Based on Zinc Oxide Nanowires
		9.2.2 (Super‐)Capacitors
	9.3 Energy Harvesting and Generators
		9.3.1 The Generator
		9.3.2 Harvesting Mechanical Energy and the Piezoelectrical Effect
		9.3.3 Ultrasonic Energy
		9.3.4 Radiofrequency Harvesting
		9.3.5 Ambient Heat
		9.3.6 Adenosine Triphosphate
		9.3.7 Fuel Cells
	9.4 Saving Energy
		9.4.1 Communication
		9.4.2 Electromagnetic vs. Molecular vs. Acoustic
		9.4.3 Preprocessing, Encoding, and Aggregation
		9.4.4 Saving via Protocols
			9.4.4.1 Destructive Retrieval
			9.4.4.2 Stateless Linear Path Saving
			9.4.4.3 Obstacles
			9.4.4.4 Ring Saving
	9.5 Summary
ch10
	10.1 Time
	10.2 Synchronization
		10.2.1 Cristian\'s Algorithm
		10.2.2 Berkeley
		10.2.3 NTP
		10.2.4 Fireflies
		10.2.5 Clocking
			10.2.5.1 QCA Synchronization
			10.2.5.2 Self‐assembly Synchronization
	10.3 Logical Time
	10.4 Consistency
		10.4.1 Types of Consistencies
		10.4.2 CAP Theorem
	10.5 Randomness
		10.5.1 Pseudorandom
		10.5.2 True Random
	10.6 Summary
ch11
	11.1 Nanonetwork Safety Analysis
		11.1.1 Classical Attack Types
		11.1.2 Classical Secure System Properties
	11.2 Attack Types
		11.2.1 Gaining Physical Access
		11.2.2 Universal Attacks
			11.2.2.1 Message/Cipher Eavesdropping
			11.2.2.2 Injection Attack
			11.2.2.3 Denial of Service
		11.2.3 Attacks on Wireless Nanonetworks
			11.2.3.1 Black Hole Attacks
			11.2.3.2 Wormhole Attack
			11.2.3.3 Replay Message Attack
			11.2.3.4 Man‐in‐the‐Middle Attack
			11.2.3.5 Malware Attack
			11.2.3.6 Device Tampering
		11.2.4 Attacks on DNA/Molecular Nanonetworks
			11.2.4.1 Attractant/Repellant Attacks
			11.2.4.2 Molecular DoS/Congestion Attack
			11.2.4.3 Chemical/Physical Disruption
	11.3 Securing Nanonetworks
		11.3.1 Low‐power AES
		11.3.2 One‐Time Pads
		11.3.3 Cyclic Redundancy Check
		11.3.4 Low‐power Hashing
		11.3.5 Medium Access Control
		11.3.6 Gateway Security
	11.4 Molecular and DNA‐based Security
		11.4.1 Infeasibility of Classical Algorithms
		11.4.2 Steganography
	11.5 Summary
ch12
	12.1 From Macro to Nano
	12.2 Nanonetwork Role Models
		12.2.1 IoNT
		12.2.2 Body Area Networks
		12.2.3 Swarm‐Based Networks and Self‐organization
	12.3 Nanonetworks
		12.3.1 Acoustic Nanonetworks
		12.3.2 EMC Nanonetworks
			12.3.2.1 Nanonetworks on Chips
		12.3.3 Bacteria‐based Nanonetworks
		12.3.4 Molecular Nanonetworks
	12.4 DNA‐Based Nanonetworks
		12.4.1 And – The Distributed Consensus
		12.4.2 Thres – Exceeding a Critical Threshold
		12.4.3 Add – Basic Arithmetics
		12.4.4 Solving Arbitrary Boolean Formulas
		12.4.5 Solving Arbitrary Computations – Turing Networks
		12.4.6 Personalized Health Parameter Anomaly Detection
		12.4.7 Tile‐based Anomaly Detection
			12.4.7.1 Phase 1
			12.4.7.2 Phase 2
			12.4.7.3 Evaluation
			12.4.7.4 Realistic Simulation in the kTAM
			12.4.7.5 Analysis in the 2HAM
	12.5 Verification Methods for Nanonetworks
		12.5.1 Analytical Methods
		12.5.2 Complexity Analysis
		12.5.3 Simulation
		12.5.4 Organs‐on‐Chips
		12.5.5 Wet‐lab
	12.6 Summary
ch13
	13.1 The Process from Idea to Final Product
	13.2 Environment
		13.2.1 Biocompatibility
	13.3 Waste Disposal
	13.4 Politics and Legal Matters
	13.5 Acceptance
	13.6 Dangers and Fears
	13.7 Summary
ch14
	14.1 Summary
	14.2 The Future and Visions of Nanonetworks
		14.2.1 Near Future
		14.2.2 Middle Future
		14.2.3 Distant Future
	14.3 Key Message
index
biblio