Internet of Things (IT-703 (B)) - Unit 1 Short Notes

UNIT 1: Internet of Things

1. Introduction to IoT

Definition & Concept

IoT is a system of interrelated computing devices, mechanical and digital machines, objects, animals, or people provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.
Ecosystem: Consists of Things (smart objects), Connectivity (networks), Data Processing (cloud/edge), and Applications (user services).

Characteristics of IoT Systems

• Connectivity: Seamless communication between devices.

• Heterogeneity: Diverse devices, protocols, and platforms.

• Scalability: Ability to handle growing numbers of devices.

• Intelligence: Embedded analytics and decision-making.

• Dynamic & Self-adapting: Devices adjust to context.

• Security & Privacy: Critical due to data sensitivity.

Evolution from M2M to IoT

• M2M (Machine-to-Machine): Direct communication between devices via point-to-point links, often proprietary, with limited intelligence.

  Example: SCADA systems.

• Shift to IoT: Driven by:

  • Cost Reduction: Cheaper sensors and connectivity.

  • Standardization: IP-based protocols enable interoperability.

  • Scalability: Cloud computing supports massive device counts.

  • Data Analytics: IoT generates big data for insights.

  • Intelligence: Edge computing and AI integration.

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Common Pitfall: M2M is device-centric with isolated systems; IoT is data-centric with integrated, internet-connected ecosystems.

IoT Architectural Frameworks

• Reference Architecture: Defines components and their interactions. Common models:

  • Three-Layer: Perception (sensors), Network (gateways/internet), Application (services).

  • Five-Layer: Perception, Transport, Processing, Application, Business.

• Information Model: Describes data semantics, relationships, and constraints (e.g., using XML/JSON schemas).

• Service-Oriented Architecture (SOA): Services are loosely coupled, reusable components.

  Challenges: Overhead, complexity in resource-constrained devices.

• Level-Based Systems:

  • Level 3: Device, Gateway, Cloud (basic integration).

  • Level 4: Adds Business Layer for analytics and monetization.

• IoT Planes & Enablers: Planes (Device, Communication, Management, Service) depend on enablers (Sensors, Actuators, Connectivity, Security, Data Analytics).

Physical vs Logical Design

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Exam Focus: Differentiate by Physical = tangible hardware; Logical = software architecture and data handling.

IoT Enablers

Key technologies that make IoT feasible:

• Sensors & Actuators: Interface with physical world.

• Connectivity: RF, cellular, LPWAN.

• Processing: Microcontrollers, SBCs, cloud.

• Security: Encryption, authentication.

• Data Analytics: AI/ML for insights.

2. IoT Devices and Components

IoT Device Design: Challenges & Requirements

• Challenges: Power constraints, size/cost, interoperability, security, real-time processing.

• Requirements: Low energy consumption, robustness, scalability, secure boot, OTA updates.

Sensors

• Evolution: From mechanical (e.g., mercury thermometer) to smart sensors with embedded processing and communication.

• Importance: Bridge physical world to digital; primary data sources.

• Types:

  | Category | Description | Examples | |----------------|------------------------------------------|----------------------------------| | Scalar | Measure single quantity | Temperature, pressure | | Vector | Measure multiple components | Accelerometer, gyroscope | | Analog | Continuous output signal | Thermocouple, potentiometer | | Digital | Discrete output (binary) | DS18B20 (temperature), PIR motion|

• Common Commercially Available Sensors:

  • Temperature: DHT22, LM35.

  • Humidity: DHT11.

  • Motion: PIR (HC-SR501).

  • Light: LDR, photodiode.

  • Gas: MQ series (MQ-2, MQ-135).

• Key Features: Accuracy, precision, range, sensitivity, response time, power consumption.

• Sensor Errors:

  • Bias: Fixed offset from true value. Calibration needed.

  • Drift: Output change over time for constant input. Aging effect.

  • Hysteresis: Difference in output for increasing vs decreasing input. Memory effect.

  • Quantization Error: Error due to analog-to-digital conversion. For step size $\Delta$, max error is $$\displaystyle \pm \frac{\Delta}{2} $$.

    \boxed{\text{Max Quantization Error} = \pm \frac{\Delta}{2}}

• Selection Criteria: Accuracy, cost, environmental robustness, power, interface (SPI/I2C/analog).

Actuators

• Role: Convert electrical/control signals into physical action (e.g., move, heat, switch).

• Functionality: Receive command from controller, produce mechanical work.

• Types:

  | Type | Description | Examples | |-------------------------|------------------------------------------|----------------------------------| | Mechanical | Electric motors, solenoids | DC motor, servo motor | | Soft | Flexible, compliant materials | Silicone grippers | | SMP-based | Shape Memory Polymers (change shape with temperature) | Self-deploying structures | | Pneumatic | Uses compressed air | Air cylinders, vacuum grippers |

• Common Selection Characteristics:

  1. Force/Torque Output: Required mechanical work.

  2. Speed/Response Time: How fast actuator moves.

  3. Precision/Accuracy: Positioning or movement control.

  4. Power Consumption: Especially for battery-operated devices.

  5. Environment: Temperature, humidity, corrosion resistance.

  6. Size & Weight: Form factor constraints.

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Exam Focus: Compare actuator types by principle, application, and pros/cons. E.g., pneumatic = safe (no sparks), but requires air supply.

Microcontrollers & Single-Board Computers (SBCs)

• Basic Review of Microcontrollers: Integrated circuits with CPU, memory (RAM/ROM), I/O peripherals (timers, ADC, communication interfaces). Low cost, low power, real-time operation.

• Arduino:

  • Features: Open-source, easy-to-use IDE, extensive libraries, GPIO pins, analog/digital I/O.

  • Role in IoT: Prototyping, simple data acquisition/control, low-cost nodes.

• Raspberry Pi:

  • Features: Full-fledged SBC with OS (Linux), HDMI/USB/Ethernet, GPIO, camera port. More processing power than microcontrollers.

  • Role in IoT: Edge gateway, complex data processing, multimedia applications.

• Interfacing:

  • SPI (Serial Peripheral Interface): Synchronous, full-duplex, master-slave. Fast, short-distance. Used for displays, SD cards.

  • I2C (Inter-Integrated Circuit): Synchronous, multi-master, two-wire (SDA, SCL). Addressable devices. Used for sensors, EEPROM.

  • GPIO (General Purpose Input/Output): Software-configured pins for digital input/output.

• Raspberry Pi vs Desktop Computers:

  | Aspect | Raspberry Pi | Desktop PC | |------------------|-------------------------------------------|------------------------------------| | Processor | ARM (low power) | x86/x64 (high performance) | | OS | Linux (Raspbian) | Windows/Linux/macOS | | Storage | SD card (no HDD/SSD) | HDD/SSD | | Power | 5V DC, low consumption | 120/240V AC, high consumption | | Use Case | Embedded, IoT prototyping | General computing |

3. Enabling Technologies

RFID (Radio Frequency Identification)

• Principles: Uses electromagnetic fields to automatically identify and track tags attached to objects. Components: Tag (with ID), Reader (emits RF, receives response), Middleware (data processing).

• Working Mechanism:

  1. Reader emits RF signal.

  2. Tag (passive/active) receives energy, modulates signal with ID.

  3. Reader captures reflected signal, decodes ID.

• Features: Non-contact, unique ID, read/write capability (some tags), varies by frequency (LF, HF, UHF).

• Terminology: Tag (transponder), Reader (interrogator), Antenna, Backscatter, EPC (Electronic Product Code).

• Applications: Inventory management, access control, asset tracking, payment systems.

• Link to IoT: Provides unique identification for "things"; foundational for object virtualization in IoT.

NFC (Near Field Communication)

• Definition: Short-range (≤4 cm) wireless technology operating at 13.56 MHz, based on RFID standards.

• Working Principle: Magnetic induction between two loop antennas. Devices must be in close proximity. Supports peer-to-peer, card emulation, reader/writer modes.

• Applications in IoT:

  • Smart posters (tap to get info).

  • Device pairing (e.g., configure Wi-Fi credentials).

  • Contactless payments.

  • Access control (smart locks).

Wireless Sensor Networks (WSN)

• Relation between WSN and IoT: WSN is the perception layer in IoT architecture. WSNs provide the sensing infrastructure that feeds data into the IoT ecosystem.

• Applications:

  • Environmental monitoring (forest fires, pollution).

  • Precision agriculture.

  • Health monitoring (wearables).

  • Industrial automation.

• Issues in IoT LAN Development:

  • Interference: Co-channel interference in dense deployments.

  • Scalability: Managing thousands of nodes.

  • Power Management: Battery life of sensor nodes.

  • Security: Vulnerable to eavesdropping, node capture.

  • Heterogeneity: Integrating diverse sensors and protocols.

4. IoT Communication and Networking

Wireless Communication Methods

• Radio Frequency (RF): Most common (Wi-Fi, Bluetooth, ZigBee, cellular).

• Optical: Infrared (IR), visible light (Li-Fi) – limited range, line-of-sight.

• Acoustic: Ultrasound – short-range, used in some indoor positioning.

Short-Range Wireless Protocols

• IEEE 802.15.4:

  • Defines PHY and MAC layers for low-rate WPANs.

  • Relation to IoT: Foundation for ZigBee, 6LoWPAN. Low power, low data rate (250 kbps), supports star/mesh topologies.

• ZigBee:

  • Architecture (based on 802.15.4):

    • Physical/MAC: From 802.15.4.

    • Network/ Security: ZigBee Network Layer (routing, addressing).

    • Application: ZigBee Device Objects (ZDO), Application Framework (profiles).

  • Types:

    • ZigBee PRO (ZigBee 2007): For mesh networks (home automation, sensor networks).

    • ZigBee IP: Adds IPv6 support, larger networks.

    • ZigBee RF4CE: Consumer electronics (remote controls).

  • Device Roles: Coordinator (forms network), Router (extends network), End Device (sleeps, low power).

• Bluetooth in IoT:

  • Bluetooth Low Energy (BLE): Optimized for low power, intermittent data. Used in wearables, beacons.

  • Classic Bluetooth: Higher bandwidth, audio streaming.

IP-Based Protocols for IoT

• IPv6:

  • Impact on IoT: 128-bit address space (~3.4×10³⁸ addresses) solves IPv4 exhaustion. Enables every device to have a unique IP. Features: autoconfiguration (SLAAC), built-in security (IPsec), efficient header.

• 6LoWPAN (IPv6 over Low-Power WPAN):

  • Role: Adaptation layer enabling IPv6 packets over IEEE 802.15.4 (or other low-power links).

  • Contribution: Header compression (reduces 40-byte IPv6 header to ~1-2 bytes), fragmentation/reassembly, stateless address autoconfiguration.

  • Differences from IPv4/IPv6:

    | Aspect | IPv4/IPv6 | 6LoWPAN | |------------------|----------------------------------------|--------------------------------------| | Layer | Network layer | Adaptation layer (between MAC & IP) | | MTU | 1500 bytes (Ethernet) | 127 bytes (802.15.4) | | Header | Fixed (IPv6: 40 bytes) | Compressed (often < 10 bytes) | | Fragmentation| Not typically at network layer | Required due to small MTU |

Network Topologies & Connection Types

• Topologies:

  • Star: All nodes connect to central hub (gateway). Simple, but hub is single point of failure.

  • Mesh: Nodes interconnect; multi-hop routing. Robust, scalable (e.g., ZigBee mesh).

  • Tree: Hierarchical; clusters with parent-child nodes.

• Connection Types:

  • Point-to-Point: Direct link between two devices.

  • Broadcast: One-to-many (e.g., Wi-Fi AP to stations).

  • Multicast: One-to-group.

IoT Gateways

• Functionality: Protocol translation (e.g., ZigBee to Wi-Fi), data aggregation, security (firewall, encryption), local processing, device management.

• Role in Ecosystem: Edge node bridging constrained devices to the internet/cloud. Acts as a mediator between local networks and wide-area networks.

IoT Communication Models

1. Device-to-Cloud: Direct connection (e.g., sensor → MQTT broker via Wi-Fi).

2. Device-to-Gateway: Through a gateway (common for non-IP devices).

3. Device-to-Device: Peer-to-peer (e.g., Bluetooth LE).

Software Defined Networking (SDN) in IoT

• Concept: Separates control plane (centralized controller) from data plane (switches). Enables flexible, programmable network management.

• Benefits for IoT: Dynamic traffic management, security policy enforcement, resource optimization.

• Challenges: Scalability of controller, overhead in constrained networks, security of control channel.

5. Application Layer Protocols

MQTT (Message Queuing Telemetry Transport)

• Example: Temperature sensor publishes to topic home/livingroom/temp; mobile app subscribes to receive updates.

• Role in IoT: Lightweight publish-subscribe protocol for low-bandwidth, high-latency networks. Minimizes network overhead and power usage.

• Key Components:

  • Broker: Central server handling messages.

  • Client: Publisher or subscriber (device/application).

  • Topic: Hierarchical string (e.g., sensors/temperature).

  • QoS Levels:

    • 0: At most once (fire-and-forget).

    • 1: At least once (acknowledgment required).

    • 2: Exactly once (two-phase handshake).

• WebSockets with MQTT: Enables MQTT over TCP/IP for web browsers (full-duplex communication over HTTP).

CoAP (Constrained Application Protocol)

• Basics: RESTful protocol for constrained devices (low power, low memory). Uses UDP (lightweight) with optional reliability.

• Use in Constrained Networks: Minimal header (4 bytes), supports multicast, observe pattern for notifications.

• Request-Response Model:

  • Client sends CON (confirmable) or NON (non-confirmable) request.

  • Server responds with ACK (for CON) or separate CON/NON.

  • Supports GET, POST, PUT, DELETE methods.

• Message Types:

  | Type | Description | |----------|------------------------------------------| | CON | Confirmable (requires ACK) | | NON | Non-confirmable (no ACK) | | ACK | Acknowledgment for CON | | RST | Reset (error or unknown request) |

• Basic Operations: GET (retrieve), POST (create), PUT (update), DELETE.

AMQP (Advanced Message Queuing Protocol)

• Features: Binary, wire-level protocol for message-oriented middleware. Reliable, secure, supports transactions.

• Components:

  • Producer: Sends messages.

  • Consumer: Receives messages.

  • Broker: Routes messages via exchanges to queues.

  • Queue: Holds messages until consumed.

  • Exchange: Receives messages from producers and routes to queues based on rules (direct, topic, fanout, headers).

• Frame Types (AMQP 1.0):

  • OPEN, BEGIN, ATTACH, SEND, FLOW, TRANSFER, DISPOSITION, DETACH, END, CLOSE.

  • Common: TRANSFER carries message payload.

• Message Attributes & Payload:

  • Attributes: message-id, user-id, to, subject, content-type, correlation-id.

  • Payload: Actual data (binary/string).

XMPP (Extensible Messaging and Presence Protocol)

• Definition: XML-based protocol for real-time messaging, presence, and request-response.

• Role in IoT Communication: Enables decentralized, secure, extensible messaging between devices. Supports pub/sub via XMPP extensions (XEPs).

• How it Improves IoT Services:

  • Presence: Devices can publish status (online/offline).

  • Extensibility: Custom Stanza (XML elements) for IoT data.

  • Security: TLS encryption, SASL authentication.

  • Scalability: Federated servers (no central broker).

SMQTT (Secure MQTT)

• Secure Message Transfer Mechanisms:

  • Encryption: TLS/SSL for data in transit.

  • Authentication: Username/password, client certificates.

  • Authorization: ACLs (Access Control Lists) on topics.

  • Key Management: Pre-shared keys or PKI.

  • Enhances standard MQTT with security without changing protocol semantics.

WebSockets

• Provides full-duplex communication over a single TCP connection. Used in IoT for real-time web dashboards (e.g., MQTT over WebSockets).

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Protocol Selection:

• MQTT: Pub/sub, low overhead, cloud-centric.

• CoAP: RESTful, UDP, device-to-device.

• AMQP: Enterprise, reliable, complex routing.

• XMPP: Real-time, presence, decentralized.

6. Cloud Computing and Data Analytics in IoT

Role of Cloud Computing in IoT

• Storage: Massive scalable storage for sensor data (e.g., AWS S3, Azure Blob).

• Processing: Compute resources for analytics, ML models (e.g., AWS Lambda, Azure Functions).

• Scalability: On-demand resources handle device spikes.

• Device Management: Provisioning, monitoring, updates.

• Integration: APIs for third-party services.

Cloud Service Models

Cloud Communication APIs

• RESTful APIs: HTTP-based for device-cloud interaction (e.g., AWS IoT Device SDK).

• MQTT/CoAP APIs: For lightweight messaging (cloud as broker).

• Role: Abstract underlying infrastructure, provide standardized interfaces for device registration, data ingestion, command delivery.

Cloud IoT Integration: Challenges & Examples

• Challenges:

  • Security: Data breaches, insecure APIs.

  • Latency: Round-trip to cloud may be too slow for real-time control.

  • Bandwidth Costs: High data volume from many devices.

  • Standardization: Lack of universal protocols.

  • Vendor Lock-in: Proprietary cloud services.

• Practical Examples:

  • AWS IoT: Devices use MQTT to AWS IoT Core; rules engine routes to Lambda, S3, DynamoDB.

  • Azure IoT Hub: Supports MQTT, AMQP; integrates with Stream Analytics.

  • Overcoming Challenges: Use edge computing to preprocess data; implement mutual TLS; adopt open standards (e.g., oneM2M).

Data Analytics in IoT

• Role: Extract insights from raw sensor data: anomaly detection, predictive maintenance, optimization.

• Difference from M2M Analytics:

  | Aspect | M2M Analytics | IoT Analytics | |------------------|------------------------------------------|---------------------------------------| | Data Volume | Low, structured | High, unstructured (big data) | | Velocity | Batch processing | Real-time/streaming | | Variety | Single source | Multi-source (sensors, social, GPS) | | Techniques | Simple statistics, rule-based | ML, AI, deep learning, stream processing |

7. Security and Privacy in IoT

Why Security is Required in IoT

• Critical Infrastructure: IoT controls physical systems (power grids, medical devices).

• Data Sensitivity: Personal data (health, location) at risk.

• Attack Surface: Many devices with weak security become entry points.

• Privacy: Continuous monitoring can violate user privacy.

Security Models in IoT

• Layered Security: Defense-in-depth across device, network, cloud.

• CIA Triad: Confidentiality, Integrity, Availability adapted for IoT.

• Zero Trust: Never trust, always verify (device authentication, encrypted comms).

• Privacy by Design: Embed privacy into system architecture (data minimization, anonymization).

Vulnerabilities in IoT Systems

• Hardware: Tampering, side-channel attacks.

• Software: Insecure firmware, unpatched vulnerabilities.

• Network: Open ports, weak encryption.

• Cloud: Insecure APIs, misconfigurations.

• Device Management: Weak default passwords, no OTA updates.

Attacks on IoT Systems

• General Attacks:

  • DDoS: Botnets (e.g., Mirai) flood targets.

  • Eavesdropping: Intercept unencrypted traffic.

  • Replay: Resend captured messages.

  • Physical Tampering: Device capture, reverse engineering.

• Application/Service Layer Attacks:

  • Injection: SQL/command injection via APIs.

  • Spoofing: Fake device identities.

  • Denial-of-Service: Overwhelm application servers.

  • Man-in-the-Middle: Intercept/alter messages between device and cloud.

Security and Privacy Issues

• Issues: Lack of standardization, resource constraints limiting security, user unawareness, data ownership ambiguity.

• Privacy Concerns: Profiling, location tracking, unauthorized data sharing.

Security Aspects in IoT Protocols

• SMQTT: Adds TLS encryption, certificate-based authentication.

• CoAP: Supports DTLS (Datagram TLS) for security.

• MQTT: TLS/SSL for encryption, username/password or client certs for auth.

• General: Use of strong ciphers, regular key rotation, secure boot.

8. IoT Platforms and Applications

IoT Platforms: Role in Development and Management

• Functions: Device onboarding, data ingestion, storage, analytics, application enablement, visualization.

• Examples: AWS IoT, Azure IoT, Google Cloud IoT, ThingWorx, IBM Watson IoT.

• Benefits: Reduce development time, manage scale, provide security, integrate with cloud services.

Hardware Platforms

• Arduino:

  • Features: ATmega microcontrollers, easy programming (Arduino IDE), vast shield ecosystem.

  • Role: Rapid prototyping, simple control tasks, education.

• Raspberry Pi:

  • Features: Broadcom SoC, Linux OS, HDMI/USB/Ethernet, GPIO, camera port.

  • Role: Edge computing, gateway, multimedia applications, complex processing.

Case Study: Smart Home Automation System

• Design with Raspberry Pi and Hardware Devices:

  • Central Hub: Raspberry Pi 4 running Home Assistant or custom Python app.

  • Sensors: DHT22 (temp/humidity), PIR (motion), LDR (light), door/window contacts.

  • Actuators: Relays for lights/fans, servo for locks, IR blaster for AC.

  • Connectivity:

    • Non-IP Devices: ZigBee modules (via USB dongle) or RF (433 MHz) for sensors/actuators.

    • IP Devices: Wi-Fi for Pi, Bluetooth for wearables.

  • Communication: MQTT broker (Mosquitto) on Pi; sensors publish to topics; actuators subscribe.

  • Cloud Integration: Pi forwards data to AWS IoT Core for remote access/analytics.

  • User Interface: Mobile app (React Native) or web dashboard (Grafana).

• Neat Sketch (Description for Canvas):

  DiagramCANVAS: Central Raspberry Pi connected to cloud via Wi-Fi/Ethernet. Pi has USB ZigBee coordinator, GPIO pins wired to relay modules and sensors. ZigBee devices (sensors, actuators) form a mesh. Cloud contains MQTT broker, database, and mobile app interface. Arrows show data flow from sensors → Pi → cloud → app; and commands from app → cloud → Pi → actuators.

IoT in Home Automation

• Applications: Lighting control, HVAC, security (cameras, alarms), entertainment, energy management.

• Building Blocks:

  1. Sensors: Detect state (motion, temperature, light).

  2. Actuators: Perform actions (switch, adjust).

  3. Gateway/Hub: Raspberry Pi or commercial hub (e.g., SmartThings).

  4. Communication: Wi-Fi, ZigBee, Z-Wave, Bluetooth.

  5. Cloud/Edge: Processing, storage, remote access.

  6. User Interface: Mobile app, voice assistant (Alexa/Google Home).

9. Advanced Topics and Cross-Cutting Themes

Quantization Error (Detailed)

• Occurs when converting continuous analog signal to discrete digital values.

• Formula: For an ADC with $$\displaystyle 2^n $$ bits and reference voltage $$\displaystyle V_{ref} $$, step size $$\displaystyle \Delta = \frac{V_{ref}}{2^n} $$.

  Maximum quantization error $$\displaystyle e_q = \pm \frac{\Delta}{2} $$.

  \boxed{e_q = \pm \frac{V_{ref}}{2^{n+1}}}

• Impact: Introduces noise; mitigated by oversampling and dithering.

Pneumatic Actuators

• Use compressed air to produce motion.

• Advantages: Clean (no oil), safe (no sparks), high force-to-weight ratio.

• Disadvantages: Requires air supply/compressor, slower response, leaks possible.

• IoT Use: Industrial automation, robotics (grippers).

IoT Conceptual Framework Details

• Layers:

  1. Perception Layer: Sensors/actuators, data acquisition.

  2. Network Layer: Connectivity, gateways, routing.

  3. Middleware/Service Layer: Data management, service discovery.

  4. Application Layer: Domain-specific apps.

  5. Business Layer: Analytics, monetization.

• Interdependencies: Each layer depends on lower layers for data/connectivity; upper layers add value.

Physical and Logical Design Details

• Physical: PCB design, power circuits, antenna placement, enclosure.

• Logical: OS (RTOS vs Linux), communication stack (TCP/IP, 6LoWPAN), data formats (JSON, CBOR), security protocols (TLS, DTLS).

CoAP Request-Response Model (Detailed)

• Confirmable (CON) Request: Client sends CON; server must respond with ACK (or RST). If no ACK, client retransmits (exponential backoff).

• Non-Confirmable (NON) Request: No ACK required; fire-and-forget.

• Response: Can be ACK (piggybacked response) or separate CON/NON.

• Example:

  Client → CON GET /sensors/temp → Server → ACK + 2.05 Content + payload (temperature value).

Sensor Node Features

• Low Power: Sleep modes, duty cycling.

• Processing: Microcontroller (8/32-bit), limited RAM.

• Communication: Short-range (802.15.4, BLE), low data rate.

• Sensing: Multiple sensor interfaces (I2C, SPI, analog).

• Size: Small form factor for embedding.

• Cost: <$10 for mass-produced nodes.

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Exam Focus: Be ready to draw diagrams for ZigBee architecture, IoT reference architecture, and smart home design. Know exact definitions (e.g., 6LoWPAN is an adaptation layer, not a network protocol).