Logical Design of IoT
The logical design of IoT refers to the architecture of software and systems that allow IoT devices to communicate, process, and analyze data. It defines how data flows and how components interact within the system.
Key Considerations in Logical Design:
1. Data Collection
- IoT devices gather data from sensors or other inputs.
- Must be efficient, accurate, and secure.
- Data is transmitted to cloud or local systems for further processing.
2. Data Processing
- Large volumes of real-time data are analyzed.
- Often uses cloud computing, edge computing, and AI/ML algorithms.
- The system must be scalable, fast, and fault-tolerant.
3. Data Storage
- Stores massive data sets securely and reliably.
- Storage may be cloud-based, edge-based, or hybrid.
- Depends on the specific application, volume, and retention requirements.
4. Connectivity
- Enables communication between devices and cloud systems.
- Can use various technologies: Wi-Fi, Bluetooth, LoRa, Zigbee, 5G, etc.
- Should be selected based on range, power, bandwidth, and cost.
5. Security
- Protects sensitive data and system integrity.
- Includes:
- Authentication & Authorization
- Encryption
- Data Integrity
- Secure Boot & Updates
6. User Interface (UI)
- The front-end interface through which users interact with the IoT system.
- Should be user-friendly, intuitive, and accessible across devices (mobile, desktop, etc.).
- Provides real-time monitoring, data visualization, and control features.
Communication Models of IoT
IoT systems rely on efficient communication models to enable interaction between devices and networks. These models define how devices exchange data.
1. Request–Response Model
- Based on Client-Server architecture.
- Client sends request → Server processes and responds.
- Stateless model: No memory of past interactions.
- Common in RESTful APIs, HTTP-based services.
2. Publisher–Subscriber Model
- Involves three components: Publisher, Broker, Subscriber.
- Publisher: Sends data to a topic (doesn’t know who consumes it).
- Broker: Routes messages to the right subscribers.
- Subscriber: Receives only relevant messages.
- Popular in MQTT, Kafka systems.
3. Push–Pull Model
- Involves Publishers, Consumers, and a Queue.
- Publisher pushes data into the queue.
- Consumer pulls data from the queue.
- Decouples producer and consumer.
- Useful when there’s a difference in data generation and consumption rates.
4. Exclusive Pair Model
- Full-duplex, bi-directional communication.
- Client and server maintain a persistent connection.
- Stateful: Server knows all active connections.
- Commonly implemented using WebSocket APIs.
Summary
| Model | Nature | Components | Use Cases |
|---|---|---|---|
| Request-Response | Stateless | Client, Server | REST APIs, HTTP communication |
| Publisher-Subscriber | Event-driven | Publisher, Broker, Subscriber | MQTT, Kafka |
| Push-Pull | Buffered | Producer, Queue, Consumer | Messaging queues (e.g. RabbitMQ) |
| Exclusive Pair | Stateful, Bi-dir | Client, Server (persistent channel) | WebSocket-based apps |