Concepts, Applications, Experimentation and Analysis of Wireless Sensor Networks: Concepts, Applications, Experimentation and Analysis

Preface
Contents
About the Author
List of Acronyms
List of Figures
List of Tables
Part I: WSNs Concepts and Applications
	Chapter 1: Introduction
		1.1 Sensing, Senses, and Sensors
		1.2 Preliminaries of Wireless Sensor Networks
		1.3 Mobile Ad Hoc Networks (MANETs)
		1.4 Wireless Mesh Networks (WMNs)
		1.5 Closer Perspective to WSNs
			1.5.1 Wireless Sensor Nodes
			1.5.2 Architecture of WSNs
		1.6 Types of WSNs
			1.6.1 Terrestrial WSNs
			1.6.2 Underground WSNs
			1.6.3 Underwater Acoustic Sensor Networks (UASNs)
			1.6.4 Multimedia WSNs
			1.6.5 Mobile WSNs
		1.7 Performance Metrics of WSNs
		1.8 WSN Standards
			1.8.1 IEEE 802.15.4 Low-Rate WPANs
			1.8.2 ZigBee
			1.8.3 WirelessHART
			1.8.4 ISA100.11a
			1.8.5 6LoWPAN
			1.8.6 IEEE 802.15.3
			1.8.7 Wibree, BLE
			1.8.8 Z-Wave
			1.8.9 Impulse Radio Ultra-Wide Bandwidth Technology, 802.15.4a
			1.8.10 INSTEON
			1.8.11 Wavenis
			1.8.12 ANT
			1.8.13 MyriaNed
			1.8.14 EnOcean
		1.9 Conclusion for a Beginning
		1.10 Exercises
		References
	Chapter 2: Protocol Stack of WSNs
		2.1 Introduction
		2.2 Physical Layer
		2.3 Data Link Layer
		2.4 Network Layer
		2.5 Transport Layer
		2.6 Application Layer
		2.7 Cross-Layer Protocols for WSNs
		2.8 Conclusion for Continuation
		2.9 Exercises
		References
	Chapter 3: WSN Applications
		3.1 Applications Categories, Challenges, and Design Objectives
			3.1.1 Functional Challenges of Forming WSNs
			3.1.2 Design Objectives of WSNs
		3.2 Military Applications
			3.2.1 Countersniper System for Urban Warfare
				3.2.1.1 Architecture
					Hardware Platform
					Software Structure
				3.2.1.2 Detection
				3.2.1.3 Routing Integrated Time Synchronization
				3.2.1.4 Sensor Fusion
					Range Estimation
				3.2.1.5 Experimentation
			3.2.2 Shooter Localization and Weapon Classification with Soldier-Wearable Networked Sensors
				3.2.2.1 Hardware
				3.2.2.2 Software Architecture
				3.2.2.3 Detection Algorithm
				3.2.2.4 Sensor Fusion
				3.2.2.5 Results
			3.2.3 Shooter Localization Using Soldier-Worn Gunfire Detection Systems
				3.2.3.1 Mathematical Formulation
				3.2.3.2 Data Fusion at Sensor Node Level
				3.2.3.3 Data Fusion at the Central Node
				3.2.3.4 Results
		3.3 Industrial Applications
			3.3.1 On the Application of WSNs in Condition Monitoring and Energy Usage Evaluation for Electric Machines
				3.3.1.1 Energy Evaluation and Condition Monitoring
					Energy Usage Evaluation
					Condition Monitoring
					Additional Requirements
				3.3.1.2 Energy Evaluation and Condition Monitoring using WSNs
					System Description
					Energy Usage Evaluation
					Motor Condition Monitoring
					Applicability Analysis
				3.3.1.3 Experimentation Results
					Energy Usage Evaluation: Motor Efficiency Estimation
					Condition Monitoring – Detection of Air-Gap Eccentricities
			3.3.2 Breath: An Adaptive Protocol for Industrial Control Applications Using WSNs
				3.3.2.1 System Setup
				3.3.2.2 The Breath Protocol
				3.3.2.3 The Breath Protocol Stack
				3.3.2.4 State Machine Description
				3.3.2.5 Results and Experimentation
			3.3.3 Requirements, Drivers, and Analysis of WSN Solutions for the Oil and Gas Industry
				3.3.3.1 Technical Requirements
					Long Battery Lifetime
					Quantifiable Network Performance
					Friendly Coexistence with WLAN
					Security
					Open Standardized Systems
				3.3.3.2 Proprietary Solutions Based on IEEE 802.15.4
				3.3.3.3 SmartMesh Experimentation and Interpretations
					Network Performance
					Coexistence with IEEE 802.11b
					Power Consumption
					Security
					Open Standardized Systems
		3.4 Environmental Applications
			3.4.1 Assorted Applications
				3.4.1.1 Large-Scale Habitat Monitoring
				3.4.1.2 Environmental Monitoring
				3.4.1.3 Precision Agriculture
				3.4.1.4 Macroscope in the Redwoods
				3.4.1.5 Active Volcano Monitoring
				3.4.1.6 Sensor and Actuator Networks on the Farm
				3.4.1.7 Cultural Property Protection
				3.4.1.8 Underground Structure Monitoring
				3.4.1.9 Foxhouse Project
				3.4.1.10 SensorScope for Environmental Monitoring
				3.4.1.11 A Biobotic Distributed Sensor Network for Under-Rubble Search and Rescue
					Mobile Sensor Nodes and Biobotic Agents
					Biobotic Control Demonstrations
					Backpack Technologies for Biobots
					Sensors for Distributed Sensing and Localization
					Localization Technologies and Algorithms
					Mapping and Exploration Strategies
			3.4.2 A2S: Automated Agriculture System Based on WSN
				3.4.2.1 System Architecture
				3.4.2.2 Experimentation Results
			3.4.3 Living IoT: A Flying Wireless Platform on Live Insects
				3.4.3.1 Why Live Insects?
				3.4.3.2 Self-Localization of Insects
				3.4.3.3 Living IoT Project Design
				3.4.3.4 Realized Outcomes
			3.4.4 Learning from Researching and Trialing
				3.4.4.1 Hardware and Software Development
					Consider Local Conditions
					Sensor Packaging
					Keep It Small and Simple
					Think Embedded
					Get All Data You Can
					Data That Is Useful
				3.4.4.2 Testing and Deployment Preparation
					Check for Interferences
					Data You Can Trust
					Be Consistent
				3.4.4.3 Deployments
					Consider Local Conditions: Once Again
					Get a Watchdog
					Keep All Data
					Data You Can Interpret
					Traceability
		3.5 Healthcare Applications
			3.5.1 Body Area Network Subsystem
				3.5.1.1 Power Consumption
				3.5.1.2 Output Transmission Power of the Sensor Nodes
				3.5.1.3 Unobtrusiveness
				3.5.1.4 Mobility and Portability
				3.5.1.5 Real-Time Availability and Reliable Communications
				3.5.1.6 Multihop Design
				3.5.1.7 Security
			3.5.2 Personal Area Network Subsystem
				3.5.2.1 Contextual Information Acquisition and Location Tracking
				3.5.2.2 Modular and Scalable Design
				3.5.2.3 Efficient Locating Algorithms
				3.5.2.4 Energy Efficiency of the MAC Layer
				3.5.2.5 Self-Organization Between Nodes
			3.5.3 Gateway to the Wide Area Networks
				3.5.3.1 Local Processing Capability at the BAN and PAN Subsystems
				3.5.3.2 Security
			3.5.4 WANs for Healthcare Applications
			3.5.5 End-User Healthcare Monitoring Application
				3.5.5.1 Security
				3.5.5.2 Privacy
				3.5.5.3 Reliability
				3.5.5.4 Middleware Design
				3.5.5.5 Context Awareness
				3.5.5.6 Seamless Healthcare Tracking and Monitoring System
			3.5.6 Categorization and Design Features of WSN Healthcare Applications
				3.5.6.1 Applications Prototypes
				3.5.6.2 Wearable and Implantable Systems
				3.5.6.3 Design Features of WSN Healthcare Applications
			3.5.7 Using Heterogeneous WSNs in a Telemonitoring System for Healthcare
				3.5.7.1 SYLPH Platform
				3.5.7.2 SYLPH Services
				3.5.7.3 SYLPH Directory Nodes
				3.5.7.4 Telemonitoring System Implementation
				3.5.7.5 Experimentation Results
		3.6 Daily Life Applications
			3.6.1 An Intelligent Car Park Management System Based on WSNs
				3.6.1.1 Car Parks Requirements
				3.6.1.2 System Overview
					Hardware Components
					Structure of the WSN-Based Application System
					Intelligent Car Park Management System
				3.6.1.3 System Implementation
					Functional Components of the System
					Event-Driven Processing
				3.6.1.4 System Evaluation
			3.6.2 Wireless Sensor Networking of Everyday Objects in a Smart Home Environment
				3.6.2.1 Requirements for WSNs in Smart Home Environments
				3.6.2.2 System Overview
					Wireless Personal Area Network
					Personal Server Running an Activity-Centered Computing Middleware
					Experimental Setup
					System Evaluation
						Wireless Communication: Transmission-Reception Range and Signal Strength Measures
						Sensing Precision and Recall Values
			3.6.3 What Else?
		3.7 Multimedia Applications
			3.7.1 Network Architecture
			3.7.2 Design Issues of WMSNs
			3.7.3 WMSN Applications
			3.7.4 Hardware Platforms of WMSNs
				3.7.4.1 Classification of Wireless Motes
				3.7.4.2 Camera Motes Features
				3.7.4.3 Available Camera Mote Platforms
					Cyclops
					Panoptes
					Address-Event Imagers
					eCAM
					WiSN
					FireFly Mosaic
					MeshEye
					MicrelEye
					WiCa
					CITRIC
					ACME Fox Board Camera Platform
					Vision Mesh
				3.7.4.4 Distributed Smart Cameras
					Occlusion
					Pixels on Target
					Field of View
					Tracking
		3.8 Robotic WSNs (RWSNs)
			3.8.1 Mobility in WSNs
			3.8.2 Robotics and WSNs
				3.8.2.1 What Is a RWSN?
				3.8.2.2 What Kind of Research Works Are RWSN Related?
				3.8.2.3 What Are the System Components and Algorithms Required for RWSNs?
		3.9 Conclusion for Further
		3.10 Exercises
		References
	Chapter 4: Transport Protocols for WSNs
		4.1 Presumptions and Considerations of Transport Protocols in WSNS
		4.2 Obsessions of Transport Protocols for WSNs
			4.2.1 Transport Protocol Performance Metrics
				4.2.1.1 Energy Efficiency
				4.2.1.2 Reliability
				4.2.1.3 QoS Metrics
				4.2.1.4 Fairness
			4.2.2 Congestion Control
			4.2.3 Loss Recovery
				4.2.3.1 Loss Detection and Notification
				4.2.3.2 Retransmission-Based Loss Recovery
		4.3 Transport Protocols for WSNs
			4.3.1 Congestion Detection and Avoidance (CODA)
			4.3.2 Event-to-Sink Reliable Transport (ESRT)
			4.3.3 Reliable Multi-Segment Transport (RMST)
			4.3.4 Pump Slowly Fetch Quickly (PSFQ)
			4.3.5 GARUDA
			4.3.6 Tiny TCP/IP
			4.3.7 Sensor TCP (STCP)
			4.3.8 SenTCP
			4.3.9 Trickle
			4.3.10 Fusion
			4.3.11 Asymmetric and Reliable Transport (ART)
				4.3.11.1 Reliable Query Transfer
				4.3.11.2 Reliable Event Transfer
				4.3.11.3 Distributed Congestion Control
			4.3.12 Congestion Control and Fairness for Many-to-One Routing in Sensor Networks (CCF)
			4.3.13 Priority-Based Congestion Control Protocol (PCCP)
			4.3.14 Siphon
			4.3.15 Reliable Bursty Convergecast (RBC)
			4.3.16 More TCP Protocols for WSNs
		4.4 Conclusion for Enrichment
		4.5 Exercises
		References
	Chapter 5: Cross-Layer Protocols for WSNs
		5.1 Why Cross-Layering in WSNs
		5.2 Cross-Layer Design Approaches
			5.2.1 Layers Interactions
				5.2.1.1 Cross-Layering MAC and Network Layers
					Cross-Layer Network Formation for Energy-Efficient IEEE 802.15.4/ZigBee WSNs (PANEL)
					A Cross-Layer Routing Protocol for Balancing Energy Consumption in WSNs (CLB)
				5.2.1.2 Cross-Layering Physical and MAC and Network Layers
					Cross-Layer Optimized Routing in WSNs with Duty-Cycle and Energy Harvesting (TPGFPlus)
			5.2.2 Single-Layer Integrated Module
				5.2.2.1 A Cross-Layer Protocol for Efficient Communication in WSNs (XLP)
		5.3 Cross-Layer Design for WSNs Security
			5.3.1 Challenges of Layered Security Approaches
			5.3.2 Limitations of Layered Security Approaches
			5.3.3 Guidelines for Securing WSNs
			5.3.4 Trends in Cross-Layer Design for Security
			5.3.5 Proposals for Cross-Layer Design for Security
		5.4 Conclusion for Reality
		5.5 Exercises
		References
Part II: WSNs Experimentation and Analysis
	Chapter 6: Testbeds for WSNs
		6.1 WSN Testbeds Principles
			6.1.1 Requirements from Testbeds Deployment
				6.1.1.1 Additional Requirements
				6.1.1.2 User Requirements from a Testbed
				6.1.1.3 Operator Requirements from a Testbed
			6.1.2 Full-Scale and Miniaturized Testbeds
			6.1.3 Virtualizing and Federating Testbeds
				6.1.3.1 Virtual Links and Federated Testbeds
				6.1.3.2 Topology Virtualization
		6.2 Testbeds Illustrated
			6.2.1 ORBIT
				6.2.1.1 Hardware
					ORBIT Grid
					Outdoor Testbed
					Sandboxes
					Chassis Manager
				6.2.1.2 Software
					Experiment Control
					Measurement and Result Collection
			6.2.2 MoteLab
				6.2.2.1 Technical Details
					MoteLab Hardware
					MySQL Database Back-End
					Web Interface
					DBLogger
					Job Daemon
					User Quotas, Direct Node Access, and Power Measurement
				6.2.2.2 Use Models
					Batch Use
					Real-Time Access
				6.2.2.3 MoteLab Applications
			6.2.3 Meerkats
				6.2.3.1 Hardware
				6.2.3.2 Software
					Resource Manager
					Visual Processing
					Communication
				6.2.3.3 Energy Consumption Characterization Benchmark
				6.2.3.4 Image Acquisition Analysis
			6.2.4 MiNT
				6.2.4.1 MiNT Architecture
					Core Nodes
					Controller Node
				6.2.4.2 Experimentation on MiNT
					Experiment Control
					Experiment Analysis
					Fidelity of MiNT
					MiNT Limitations
				6.2.4.3 Hybrid Simulation
					Implementation Issues
					Hybrid Simulation vs. Pure Simulation
						Signal Propagation
						Error Characteristics
			6.2.5 MiNT-m
				6.2.5.1 MiNT-m Architecture
					Hardware Components
					Software Components
				6.2.5.2 Using MiNT-m
					Experiment Configuration
					Experiment Execution
					Experiment Analysis
				6.2.5.3 Autonomous Node Mobility
					Position and Orientation Tracking
					Node Trajectory Determination
					24×7 Autonomous Operations and Auto-recharging
				6.2.5.4 Hybrid Simulation
					Pause/Breakpointing
					Rollback Execution
					Performance
			6.2.6 Kansei
				6.2.6.1 Kansei Composition
					Hardware Infrastructure
						The Stationary Array
						Portable Array
						Mobile Array
					Director: A Uniform Remotely Accessible Framework for Multi-tier WSN Applications
						Director Architecture
				6.2.6.2 High Fidelity Sensor Data Generation Tools
					Sample-Based Modeling Tools
					Synthetic Data Generation Using Parametric Models
					Probabilistic Modeling Tools
				6.2.6.3 Hybrid Simulation
			6.2.7 Trio
				6.2.7.1 Trio Architecture
					Tier-1: The Trio Node
						Sustainable Operation
						Efficient Physical Interaction
						Fail-Safe Flexibility
					Tier-2: A Network of Gateways
					Tier-3: The Root Server
						Network Health Monitoring
						Power Monitoring
						Monitoring Network Programming
						Monitoring and Control of Applications
					Tier-4: Client Applications
				6.2.7.2 Experimenting with Trio
					Familiarities with Renewable Energy
					Limited Availability
					Emergency Battery Daemon
					Epidemic Protocol Failures
					Variability at Scale
			6.2.8 TWIST
				6.2.8.1 TWIST Architecture
					Sensor Nodes
					Testbed Sockets and USB Cabling
					USB Hubs
					Super Nodes
					Server
					Control Station
				6.2.8.2 TWIST Installation
					Matching SUE and TWIST Architectures
					Programming and Time Synchronization
					Power Supply Control
					Management
				6.2.8.3 TWIST Deployment
			6.2.9 SignetLab
				6.2.9.1 Hardware
					Deployment Space
					Sensor Nodes
					Backplane Connection
				6.2.9.2 Software Tool
				6.2.9.3 Analysis of SignetLab
			6.2.10 WISEBED
				6.2.10.1 Architecture
				6.2.10.2 WISEBED Compatible Testbeds
			6.2.11 Indriya
				6.2.11.1 Indriya Composition
					Motes
					Sensors
					USB Active Cables
					Design of a Back-Channel for Remote Programming
					User Interface
				6.2.11.2 Indriya Compared
			6.2.12 GENI
				6.2.12.1 Federated WSN Fabrics
					Clearinghouse Tasks
						Federation Services
						Authorization Services
						Accountability Services
						Resource Representation
						Resource Discovery
						Resource Allocation
					Site Requirements
						Sliceability
						Virtualization
						Programmability
					Researcher Requirements
						Resource Utilization
						Resource Translation
				6.2.12.2 Why to Use GENI?
				6.2.12.3 Key GENI Concepts
					Project
					Slice
					Aggregates
					The GENI AM API and GENI RSpecs
					Getting Access to GENI and GENI Resources
					Tying up All Together: The GENI Experimenter Workflow
						Experiment Setup
						Experiment Execution
						Finishing up
			6.2.13 Further Testbeds
				6.2.13.1 Emulab
				6.2.13.2 PlanetLab
				6.2.13.3 Mobile Emulab
				6.2.13.4 SenseNet
				6.2.13.5 Ubiquitous Robotics
		6.3 Conclusion for Extension
		6.4 Exercises
		References
	Chapter 7: Simulators and Emulators for WSNs
		7.1 WSN Testbeds, Simulators, and Emulators
		7.2 Modeling and Simulation
			7.2.1 Basic Definitions
			7.2.2 Validation and Verification
		7.3 Simulation Principles and Practice
			7.3.1 Simulating the Advance of Time
				7.3.1.1 The Time-Slicing Approach
				7.3.1.2 The Discrete-Event Simulation Approach
				7.3.1.3 The Three-Phase Simulation Approach
				7.3.1.4 The Continuous Simulation Approach
			7.3.2 Proof of Concept
			7.3.3 Common Simulation Shortcomings
				7.3.3.1 Simulation Setup
					Simulation Type
					Model Validation and Verification
					PRNG Validation and Verification
					Variable Definition
					Scenario Development
				7.3.3.2 Simulation Execution
					Setting the PRNG Seed
					Scenario Initialization
					Metric Collection
				7.3.3.3 Output Analysis
					Single Set of Data
					Statistical Analysis
					Confidence Intervals
				7.3.3.4 Publishing
			7.3.4 Unreliable Simulation Revealed
			7.3.5 The Price of Simulation
		7.4 Simulators and Emulators
			7.4.1 The Network Simulator (ns-2)
			7.4.2 The Network Simulator (ns-3)
			7.4.3 GloMoSim
				7.4.3.1 Parsec
				7.4.3.2 Visualization Tool
				7.4.3.3 GloMoSim Library
				7.4.3.4 Aggregation
					Node Aggregation
					Layer Aggregation
			7.4.4 OPNET
				7.4.4.1 Hierarchical Modeling
					Network Model
					Node Model
					Process Model
				7.4.4.2 Data Generation
					Probe Editor
					Analysis Tool
					Filter Tool
			7.4.5 OMNeT++
				7.4.5.1 The Design of OMNeT++
					Model Structure
					The NED Language
					Graphical Editor
					Separation of Model and Experiments
					Simple Module Programming Model
					Design of the Simulation Library
					Parallel Simulation Support
					Real-Time Simulation and Network Emulation
					Animation, Tracing, and Visualizing Dynamic Behavior
			7.4.6 TOSSIM
			7.4.7 ATEMU
			7.4.8 Avrora
			7.4.9 EmStar
				7.4.9.1 Experimentation
					Pure Simulation
					Testbeds
					Emulation
					EmTOS
			7.4.10 SensorSim
			7.4.11 NRL SensorSim
			7.4.12 J-Sim
				7.4.12.1 ACA Overview
					Component
					Component Hierarchy
					Port
					Contract
				7.4.12.2 J-Sim Framework
					Communication Model
					Power Model
				7.4.12.3 Network Emulation
				7.4.12.4 J-Sim Performance Compared
					Target Tracking
					Using GPSR Routing Protocol
			7.4.13 Prowler/JProwler
				7.4.13.1 Prowler Framework
					Radio Propagation Models
					Signal Reception and Collisions
					MAC Layer Model
					The Application Layer
				7.4.13.2 Optimization Framework
				7.4.13.3 Prowler Performance
				7.4.13.4 JProwler
			7.4.14 SENS
				7.4.14.1 Simulator Structure
					Application Components
					Network Components
					Physical Components
					Environment Component
				7.4.14.2 Simulation Examples
					Spanning Tree
					Simplified Localization
				7.4.14.3 SENS Performance
			7.4.15 Sense
				7.4.15.1 Component-Based Design
				7.4.15.2 Sensor Network Simulation Components
				7.4.15.3 Components Repository
				7.4.15.4 Performance Comparison
			7.4.16 Shawn
				7.4.16.1 Architecture
					Models
					Sequencer
					Simulation Environment
				7.4.16.2 Shawn Compared
			7.4.17 SenSim
				7.4.17.1 SenSim Design
					Coordinator Module
					Hardware Model
					Wireless Channel Model
					Sensor Node Stack
			7.4.18 PAWiS
				7.4.18.1 Structure and Functions
					Modularization
					CPU
					Timing
					Environment and Air
					Power Simulation
					Dynamic Behavior
				7.4.18.2 Optimization
			7.4.19 MSPsim
			7.4.20 Castalia
			7.4.21 MiXiM
				7.4.21.1 MiXiM Base Models
					Environmental Model
					Connection Modeling
					Nodes Connectivity
					Wireless Channel Models
					Physical Layer Models
			7.4.22 NesCT
			7.4.23 Sunshine
				7.4.23.1 SUNSHINE Components
				7.4.23.2 SUNSHINE Functioning
				7.4.23.3 Cross-Domain Interface
				7.4.23.4 SUNSHINE Compared
			7.4.24 NetTopo
		7.5 Conclusion for Takeoff
		7.6 Exercises
		References
Part III: WSNs Manufacturers and Datasheets
	Chapter 8: WSNs Manufacturers
		8.1 Adaptive Wireless Solutions (Adaptive Wireless Solutions 2015)
		8.2 AlertMe (AlertMe 2014) and British Gas (British Gas 2015)
		8.3 ANT Wireless Division of Dynastream (Dynastream Innovations 2014)
		8.4 Atmel (Atmel 2015)
		8.5 Cisco (Cisco 2015)
		8.6 Coalesenses (Coalesenses 2014)
		8.7 Crossbow Technologies (Aol 2015)
		8.8 Dust Networks (Dust Networks 2015)
		8.9 EasySen (EasySen 2015)
		8.10 EcoLogicSense (EcoLogicSense 2015)
		8.11 EpiSensor (EpiSensor 2015)
		8.12 ERS (ERS 2015)
		8.13 GainSpan (GainSpan 2015)
		8.14 Infineon (Infineon 2015)
		8.15 Libelium (Libelium 2015)
		8.16 MEMSIC (MEMSIC 2015)
		8.17 Millennial Net (Millennial Net 2012)
		8.18 Moog Crossbow (Moog Crossbow 2014)
		8.19 Moteiv (Sensors Online 2007)
		8.20 National Instruments (National Instruments 2015)
		8.21 OmniVision Technologies (OmniVision Technologies 2011)
		8.22 Sensirion (Sensirion 2015)
		8.23 Shimmer (Shimmer 2015)
		8.24 Silicon Labs (Sillicon Labs 2015)
		8.25 SOWNet Technologies (SOWNet Technologies 2014)
		8.26 SPI (SPI 2015)
		8.27 Terabee (Terabee 2015)
		8.28 Texas Instruments (TI 2015)
		8.29 Valarm (Valarm 2015)
		8.30 WhizNets (WhizNets 2015)
		8.31 Willow Technologies (Willow Technologies 2012)
		8.32 Xandem (Xandem 2015)
		References
	Chapter 9: Datasheets
		9.1 Agilent ADCM-1670 CIF Resolution CMOS Camera Module (Agilent Technologies 2003a)
		9.2 Agilent ADCM-1700-0000 CMOS Camera Module (Agilent Technologies 2003b)
		9.3 Agilent ADCM-2650 CMOS Camera Module (Agilent Technologies 2003c)
		9.4 Agilent ADNS-3060 Optical Mouse Sensor (Agilent Technologies 2004)
		9.5 AL440B High Speed FIFO Field Memory (AverLogic Technologies 2002)
		9.6 Atmel AT29BV040A Flash Memory (Atmel 2003)
		9.7 Atmel AT91 ARM Thumb-Based Microcontrollers (Atmel 2008)
		9.8 Atmel AT91SAM ARM-Based Embedded MPU (Atmel 2011c)
		9.9 Atmel Microcontroller with 4/8/16 K Bytes In-System Programmable Flash (Atmel 2011b)
		9.10 Atmel Microcontroller with 128 K Bytes In-System Programmable Flash (Atmel 2011a)
		9.11 Atmel FPSLIC (Atmel 2002)
		9.12 Bluegiga WT12 (Bluegiga Technologies 2007)
		9.13 C8051F121 Mixed-Signal MCU (Silicon Laboratories 2004)
		9.14 CC1000 (Texas Instruments 2007a)
		9.15 CC1020 (Texas Instruments 2014a)
		9.16 CC1100 (Texas Instruments 2005a)
		9.17 CC1101 (Texas Instruments 2014b)
		9.18 CC2420 (Texas Instruments 2005b)
		9.19 CC2430 (Texas Instruments 2006)
		9.20 CC2431 (Texas Instruments 2005c)
		9.21 CC2530 (Texas Instruments 2011a)
		9.22 CP2102/9 Single-Chip USB to UART Bridge (Silicon Laboratories 2013)
		9.23 Digital Compass Solutions HMR3300 (Honeywell 2012)
		9.24 DS18B20 Programmable Resolution 1-Wire Digital Thermometer (Maxim Integrated 2008)
		9.25 DS18S20 High-Precision 1-Wire Digital Thermometer (Maxim Integrated 2010)
		9.26 G-Node G301 (SOWNet Technologies 2014)
		9.27 GS-1 Low Frequency Seismometer (Geospace Technologies 2014b)
			9.27.1 GS-1 Low Frequency Seismometer
		9.28 GS-11D Geophone (Geospace Technologies 2014a)
		9.29 Imote2 (Crossbow 2005)
		9.30 Intel PXA270 Processor (Intel 2005a)
		9.31 Intel StrataFlash Embedded Memory (Intel 2005b)
		9.32 Intel StrongARM* SA-1110 (Intel 2000)
		9.33 iSense Security Sensor Module (Coalesenses 2014)
		9.34 MICA2 Mote (Crossbow 2002a)
		9.35 MICA2DOT (Crossbow 2002b)
		9.36 MICAz Mote (Crossbow 2006a)
		9.37 ML675K Series (Oki Semiconductor 2004)
		9.38 MOTE-VIEW 1.2 (Crossbow 2006b)
		9.39 MSB-A2 Platform (Baar et al. 2008)
		9.40 MSP430F1611 Microcontroller (Texas Instruments 2011b)
		9.41 MSP430F2416 Microcontroller (Texas Instruments 2007b)
		9.42 MSX-01F Solar Panel (BP Solar 2014)
			9.42.1 BP SOLAR – MSX-01F – SOLAR PANEL, 1.2 W
		9.43 MTS/MDA (Crossbow 2007a)
		9.44 Omron Subminiature Basis Switch (Omron 2014)
		9.45 OV528 Serial Bus Camera System (OmniVision Technologies 2002)
		9.46 OV6620/OV6120 Single-Chip CMOS Digital Camera (OmniVision Technologies 1999)
		9.47 OV7640/OV7140 CMOS VGA CAMERACHIPS (OmniVision Technologies 2003)
		9.48 OV9655/OV9155 (OmniVision Technologies 2006)
		9.49 PCF50606/605 Single-Chip Power Management Unit+ (Philips 2002)
		9.50 PIC18 Microcontroller Family (Microchip 2000)
		9.51 Qimonda HYB18L512160BF-7.5 (Qimonda AG 2006)
		9.52 SBT30EDU Sensor and Prototyping Board (EasySen LLC 2008a)
		9.53 SBT80 Multi-Modality Sensor Board for TelosB Wireless Motes (EasySen LLC 2008a)
		9.54 Spartan-3 FPGA (XILINX 2013)
		9.55 Stargate (Crossbow 2004)
		9.56 Stargate NetBridge (Crossbow 2007b)
		9.57 T-Node (SOWNet 2014)
		9.58 TC55VCM208ASTN40,55 CMOS Static RAM (Toshiba 2002)
		9.59 Telos (Moteiv 2004)
		9.60 TinyNode (Dubois-Ferrière et al. 2006, Fig. 9.2)
		9.61 Tmote Connect (Moteiv 2006a)
		9.62 Tmote Sky (Moteiv 2006b)
		9.63 TSL250R, TSL251R, TSL252R Light to Voltage Optical Sensors (TAOS 2001)
		9.64 WiEye Sensor Board for Wireless Surveillance and Security Applications (EasySen LLC 2008b)
		9.65 WM8950 (Wolfson Microelectronics 2011)
		9.66 Xbee/Xbee-PRO OEM RF Modules (MaxStream 2007)
		9.67 XC2C256 CoolRunner-II CPLD (XILINX 2007)
		9.68 XE1205I Integrated UHF Transceiver (Semtech 2008)
		References
Part IV: Ignition
	Chapter 10: Takeoff
Index