385  WSN Review: Architecture and Design

385.1 Learning Objectives

By the end of this chapter, you will be able to:

  • Understand WSN Architecture: Comprehend the hierarchical organization of wireless sensor networks
  • Select Appropriate Topologies: Choose optimal network topologies based on deployment constraints
  • Evaluate Energy Trade-offs: Analyze energy consumption patterns and optimization strategies
  • Apply Architecture Decisions: Use decision trees to guide WSN deployment choices

385.2 Prerequisites

Required Chapters: - WSN Overview Fundamentals - Core WSN concepts - Wireless Sensor Networks - WSN architecture - Sensor Fundamentals - Sensor basics

Technical Background: - Sensor node architecture - Energy constraints in WSNs - Data aggregation concepts

WSN Architecture Layers:

Layer Function Example
Application User services Environmental monitoring
Transport Reliability Congestion control
Network Routing RPL, AODV
Data Link MAC access CSMA/CA, TDMA
Physical Radio 802.15.4

Estimated Time: 15 minutes

WSN Review Series: - WSN Overview Review (Index) - Series overview - WSN Review: Knowledge Checks - Quick assessment questions - WSN Review: Scenario Analysis - Detailed scenario walkthroughs - WSN Review: Comprehensive Assessment - Advanced topics and summary

WSN Overview Series: - WSN Overview Fundamentals - Core WSN concepts - Wireless Sensor Networks - Architecture and design

Advanced Topics: - WSN Coverage Fundamentals - Area and target coverage - WSN Tracking Fundamentals - Mobile target tracking

What is this chapter? This review chapter consolidates Wireless Sensor Network (WSN) architecture concepts. It’s designed to test and reinforce your understanding of WSN design decisions.

Key Concepts to Master:

Concept Why It Matters
Sensor Nodes Basic building blocks of WSNs
Network Topology How sensors connect and communicate
Data Aggregation Reducing network traffic efficiently
Energy Efficiency Maximizing battery life

Recommended Path: 1. Study WSN Overview Fundamentals first 2. Review WSN Implementations 3. Return here to test your understanding

The Misconception: Many developers assume full mesh topologies with multi-hop routing provide superior reliability and resilience compared to simple star topologies. After all, mesh networks have multiple redundant paths—what could go wrong?

The Reality - Quantified:

A 2019 smart building deployment compared mesh vs. star architectures for 200 temperature sensors:

Full Mesh Deployment (AODV routing): - Initial promise: “Multiple paths ensure reliability!” - Reality after 3 months: - Battery life: 14 hours (nodes drained overnight) - Packet delivery ratio: 67% (routing loops, collisions, overhead) - Network failures: Daily (nodes dying disrupted routing tables) - Operational cost: $182,500/year (daily battery replacements at $50/visit) - Root cause: Routing overhead (route discovery broadcasts) + relay burden consumed 3.3 Ah/day per node vs. 0.055 Ah/day for direct transmission

Star Topology with 10 Mains-Powered Gateways: - Each gateway serves 20 sensors in direct single-hop communication - Results after 12 months: - Battery life: 36+ days (60x improvement) - Packet delivery ratio: 99.2% (no routing, minimal collisions) - Network failures: Rare (gateway redundancy, no battery cascade failures) - Operational cost: $12,000/year (monthly battery service) - Total system cost: $7,000 hardware vs. mesh $9,000 (mesh needs more RAM/CPU for routing)

Why Mesh Failed: 1. Energy asymmetry: Inner nodes relayed traffic for ~10 neighbors, consuming 60x more energy than sensing alone 2. Routing overhead: AODV route discovery broadcasts flooded network every time a node moved or failed 3. Collision amplification: 200 competing transmitters created exponential backoff waste 4. The hotspot problem: Nodes near sinks died in days, creating coverage holes that isolated outer nodes

The Correct Principle: “Always ask: Can I add more gateways instead of using mesh?” The answer is usually yes, and it’s dramatically cheaper in both energy and operational cost. Mesh routing is a solution for situations where gateway placement is truly impossible—not a default architecture choice.

When Mesh Makes Sense (Rare Cases): - Sensor spacing >200m AND terrain prevents gateway placement (dense forest, mountains) - Temporary deployments where infrastructure installation is impractical (military, disaster response) - Mobile sensor networks (vehicular, UAV swarms) where fixed infrastructure doesn’t exist

Real-world Lesson: “We spent $40K on custom mesh firmware optimization, achieving 28-hour battery life. Then someone suggested adding 5 PoE gateways for $1,000. Battery life jumped to 5+ years. Sometimes the best algorithm is: don’t route.”

385.3 WSN System Architecture

⏱️ ~10 min | ⭐ Foundational | 📋 P05.C33.U01

WSN System Architecture (Hierarchical Organization)

Layer Component Function Key Features
Physical Layer Sensor Nodes (6 nodes shown) Sense & transmit data MCU + Radio + Sensors, Battery powered
Network Layer Cluster Heads (2 nodes) Data aggregation & relay Reduce traffic with statistical summaries (min/max/avg)
Gateway Layer Gateway/Sink Protocol bridge Network coordinator, Wi-Fi/Ethernet/Cellular
Application Layer Cloud Platform Storage & analytics ML, user interface, command distribution

Data Flow (Upward): Sensor Nodes → (multi-hop, 802.15.4) → Cluster Heads → (aggregated data) → Gateway → (Internet) → Cloud

Control Flow (Downward): Cloud → Gateway → Cluster Heads → Sensor Nodes (commands, configuration, actuation)

Graph diagram

Graph diagram
Figure 385.1: WSN hierarchical architecture showing four layers: Physical layer with battery-powered sensor nodes (temperature, humidity, motion, light, pressure, gas), Network layer with cluster heads performing data aggregation (min/max/avg), Gateway layer providing protocol bridge (Wi-Fi/Ethernet/Cellular), and Application layer with cloud platform for analytics, ML, and user interface. Data flows upward through multi-hop 802.15.4 to cluster heads to gateway to cloud; control commands flow downward.

%% fig-alt: "Decision tree for selecting WSN architecture components based on deployment requirements including power availability, range needs, data rate, and latency constraints"
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graph TD
    START{WSN Deployment<br/>Requirements?}

    START -->|"Power Available"| MAINS[Mains-Powered Gateway]
    START -->|"Battery Only"| BATT{Data Rate?}

    MAINS --> STAR[Star Topology<br/>802.15.4 or BLE]
    MAINS --> Wi-Fi[Wi-Fi Sensors<br/>High bandwidth]

    BATT -->|"<10 kbps"| RANGE{Range Needed?}
    BATT -->|">10 kbps"| MESH[Mesh Required<br/>Higher energy cost]

    RANGE -->|"<100m"| SHORTRANGE[802.15.4<br/>Zigbee/Thread]
    RANGE -->|">1km"| LONGRANGE[LoRaWAN<br/>NB-IoT]

    SHORTRANGE --> LATENCY{Latency?}
    LONGRANGE --> LPWAN[LPWAN<br/>5+ year battery]

    LATENCY -->|"<100ms"| REALTIME[Wake-up Radio<br/>or S-MAC]
    LATENCY -->|">1s OK"| DUTYCYCLE[Heavy Duty Cycling<br/>X-MAC]

    STAR --> RESULT1[Result: 5+ year life<br/>High reliability]
    Wi-Fi --> RESULT2[Result: High bandwidth<br/>Unlimited power]
    MESH --> RESULT3[Result: <1 month life<br/>Complex routing]
    LPWAN --> RESULT4[Result: 10+ km range<br/>Low data rate]
    REALTIME --> RESULT5[Result: Fast response<br/>Moderate energy]
    DUTYCYCLE --> RESULT6[Result: Maximum life<br/>Delayed response]

    style START fill:#2C3E50,stroke:#16A085,color:#fff
    style MAINS fill:#16A085,stroke:#2C3E50,color:#fff
    style BATT fill:#E67E22,stroke:#2C3E50,color:#fff
    style RANGE fill:#E67E22,stroke:#2C3E50,color:#fff
    style LATENCY fill:#E67E22,stroke:#2C3E50,color:#fff
    style RESULT1 fill:#16A085,stroke:#2C3E50,color:#fff
    style RESULT2 fill:#16A085,stroke:#2C3E50,color:#fff
    style RESULT3 fill:#7F8C8D,stroke:#2C3E50,color:#fff
    style RESULT4 fill:#16A085,stroke:#2C3E50,color:#fff
    style RESULT5 fill:#16A085,stroke:#2C3E50,color:#fff
    style RESULT6 fill:#16A085,stroke:#2C3E50,color:#fff

Figure 385.2: Alternative View: Architecture Selection Decision Tree: While the layered architecture diagram above shows WSN components, this decision tree helps practitioners select the right components based on deployment constraints. Start with power availability (the most critical constraint), then evaluate data rate, range, and latency requirements. Each path leads to specific technology recommendations with expected outcomes. This decision-oriented view transforms abstract architecture knowledge into actionable deployment guidance. Key insight: most architecture failures stem from ignoring the first question (power availability) and jumping directly to protocol selection. {fig-alt=“WSN architecture selection decision tree starting with power availability question, branching through data rate, range, and latency decisions, with six outcome paths showing specific technology recommendations (Star/802.15.4 for 5+ year life, Wi-Fi for high bandwidth, Mesh with energy warning, LPWAN for long range, Wake-up radio for real-time, Duty cycling for maximum battery life) - each decision node color-coded with navy for primary decisions, orange for constraints, and teal for positive outcomes”}

385.4 WSN Application Domains

WSN Application Domains

Domain Applications
Environmental Forest Fire Detection, Air Quality Monitoring, Water Quality, Weather Stations, Flood Detection
Industrial Process Monitoring, Equipment Health, Factory Automation, Supply Chain Tracking, Predictive Maintenance
Infrastructure Structural Health, Bridge Monitoring, Pipeline Leak Detection, Smart Grid, Traffic Monitoring
Agriculture Precision Farming, Soil Moisture, Crop Health, Livestock Tracking, Greenhouse Automation
Healthcare Patient Monitoring, Vital Signs, Medication Tracking, Fall Detection, Elderly Care
Military Battlefield Surveillance, Target Tracking, Intrusion Detection, Chemical Detection, Perimeter Security
Smart City Parking Management, Waste Management, Street Lighting, Noise Monitoring, Public Safety
Wildlife Animal Tracking, Habitat Monitoring, Migration Patterns, Population Studies, Conservation

Mind map diagram

Mind map diagram
Figure 385.3: WSN application domains mindmap showing eight major deployment areas: Environmental monitoring (fire, air, water quality), Industrial automation (process monitoring, predictive maintenance), Infrastructure health (bridges, pipelines, smart grid), Agriculture (precision farming, soil moisture, livestock), Healthcare (patient monitoring, fall detection), Military (surveillance, intrusion detection), Smart City (parking, waste, lighting), and Wildlife conservation (animal tracking, habitat monitoring).

385.5 WSN Energy Trade-offs

Understanding energy consumption patterns is critical for WSN deployment success:

Graph diagram

Graph diagram
Figure 385.4: WSN energy consumption breakdown showing four primary energy states: Sleep mode (1-10 µA, excellent for 5+ year battery life), Idle listening (15 mA continuous, poor - only 5 days battery life), Transmission (20 mA at 1% duty cycle, 4.8 mAh/day), and Sensing (5 mA at 0.1%, 1.2 mAh/day). Solutions include duty cycling protocols (S-MAC synchronized, X-MAC asynchronous, Wake-up radio) that enable deep sleep 99.9% of time while maintaining network responsiveness.

385.6 WSN Topology Selection Decision Tree

Choose the right topology based on deployment constraints:

Graph diagram

Graph diagram
Figure 385.5: WSN topology selection decision tree starting with mains power availability: If YES → Star topology (20-50 sensors per gateway, 5+ year battery, simple routing, best for buildings/infrastructure); If NO → Check sensor spacing: If >100m → Hierarchical clustering (LEACH rotation, 3-6 month battery for cluster heads, best for remote/forest deployments); If <100m → Star with repeaters (2-3 mains repeaters, 3+ year battery, minimal overhead, best for accessible campuses/farms/industrial sites).

385.7 Summary

This chapter covered the foundational architecture concepts for WSN review:

  • Hierarchical Architecture: Four-layer organization from physical sensors to cloud applications
  • Architecture Selection: Decision tree approach based on power, data rate, range, and latency constraints
  • Application Domains: Eight major deployment areas spanning environmental, industrial, and smart city applications
  • Energy Trade-offs: Understanding sleep vs. idle vs. transmission power consumption
  • Topology Selection: Choosing between star, mesh, and hierarchical based on constraints

385.8 What’s Next

Continue to the knowledge check questions to test your understanding of WSN architecture concepts.

Continue to WSN Review: Knowledge Checks →