433  Sensor Network Routing

433.1 Learning Objectives

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

  • Compare WSN Routing Paradigms: Distinguish data-centric, hierarchical, and geographic routing approaches
  • Implement Directed Diffusion: Configure attribute-based routing for data-centric sensor networks
  • Design Energy-Aware Routes: Select paths that balance energy consumption across network nodes
  • Apply Data Aggregation: Implement in-network data processing to reduce communication overhead
  • Evaluate Link Quality: Use link quality metrics to improve routing reliability and performance
  • Configure Trickle Algorithm: Implement efficient dissemination protocols for network updates

433.2 Prerequisites

Before diving into this chapter, you should be familiar with:

  • Wireless Sensor Networks: Understanding WSN architecture, multi-hop communication, and energy constraints provides the foundation for specialized routing protocols
  • WSN Overview: Fundamentals: Knowledge of sensor network characteristics, data aggregation, and network topologies is essential for understanding routing decisions
  • Routing Fundamentals: Familiarity with basic routing concepts, routing tables, and forwarding mechanisms helps distinguish WSN-specific routing approaches
  • Multi-Hop Ad Hoc: Fundamentals: Understanding self-organizing networks and dynamic routing provides context for data-centric and geographic routing strategies
TipMVU: Minimum Viable Understanding

Core concept: WSN routing differs fundamentally from traditional network routing because it prioritizes energy efficiency over throughput and uses data-centric approaches instead of address-based routing.

Why it matters: Sensors operate on limited batteries for years; inefficient routing drains nodes prematurely, creating coverage gaps. Traditional shortest-path routing fails because it ignores link quality, energy levels, and the many-to-one traffic pattern in sensor networks.

Key takeaway: Choose routing protocols based on your application: Directed Diffusion for event-driven data collection, LEACH for hierarchical aggregation, geographic routing when GPS is available, and always consider link quality metrics (ETX) over simple hop count.

433.3 Chapter Overview

This chapter has been organized into six focused sections for easier learning. Work through them in order, or jump to the topic most relevant to your current needs:

433.3.1 1. WSN Routing Fundamentals (3 chapters)

Introduction, challenges, and protocol classification

Routing in Wireless Sensor Networks differs fundamentally from traditional network routing. This section is organized into three focused chapters:

433.3.2 2. Directed Diffusion Protocol

Data-centric routing with interests and gradients

Directed Diffusion revolutionized WSN routing with its publish-subscribe paradigm. This section explains how sinks express “interests” and how data flows along gradients back to interested parties.

  • Interest propagation mechanism
  • Gradient establishment and data delivery
  • Two-phase pull and reinforcement
  • Protocol benefits and trade-offs

433.3.3 3. Data Aggregation Techniques

In-network processing to reduce transmissions

Data aggregation combines sensor readings to dramatically reduce transmission count and energy consumption. This section covers aggregation functions, metrics, and the LEACH clustering protocol.

  • Aggregation functions (MIN, MAX, AVG, SUM)
  • Accuracy, completeness, and latency trade-offs
  • LEACH cluster head rotation
  • Worked example: Energy analysis

433.3.5 5. Trickle Algorithm

Efficient network reprogramming

WSNs may operate for years, requiring over-the-air updates. Trickle provides “polite gossip” for code propagation with minimal overhead when consistent and rapid propagation when needed.

  • Network reprogramming challenges
  • Trickle’s suppression mechanism
  • Exponential backoff
  • Implementation parameters

433.3.6 6. Labs and Interactive Games

Hands-on practice and simulations

Apply your knowledge with interactive tools and hands-on labs that demonstrate routing protocols in action.

  • WSN Route Optimizer Game
  • Multi-hop routing simulation (Wokwi ESP32)
  • Protocol comparison exercises

433.4 Quick Reference: Protocol Selection

Scenario Recommended Protocol Rationale
Event-driven monitoring Directed Diffusion Data-centric, responds to queries
Dense deployment (>100 nodes) LEACH/PEGASIS Hierarchical aggregation scales
GPS-equipped nodes GPSR/GEAR Geographic forwarding efficient
Real-time alerts QoS protocols (SPEED) Latency guarantees
Stable topology Proactive (DSDV) Routes ready immediately
Mobile nodes Reactive (AODV) Adapts to changes
Code updates Trickle Low overhead when consistent

433.5 Key Concepts

NoteKey Concepts
  • Routing Protocol: Algorithm determining paths for data packets to travel from source sensors to destination sinks through multi-hop networks
  • Energy-Aware Routing: Protocols that select paths based on node energy levels to balance consumption and extend network lifetime
  • Data-Centric Routing: Routing based on data content rather than node addresses, enabling in-network aggregation and filtering
  • Hierarchical Routing: Organizing network into clusters with cluster heads aggregating data from members before forwarding to sinks
  • Geographic Routing: Protocols using node location information to make forwarding decisions without maintaining routing tables
  • Expected Transmission Count (ETX): Link quality metric estimating transmissions needed for successful delivery, accounting for retransmissions

433.6 What’s Next

Start with WSN Routing Fundamentals to understand why WSN routing differs from traditional networking. If you’re already familiar with WSN challenges, skip to Directed Diffusion to learn the foundational data-centric protocol.

After completing this chapter series, proceed to:

Deep Dives:

Protocols:

Reviews:

Learning:

433.7 Further Reading

  1. Intanagonwiwat, C., et al. (2003). “Directed diffusion for wireless sensor networking.” IEEE/ACM Transactions on Networking, 11(1), 2-16.

  2. Woo, A., Tong, T., & Culler, D. (2003). “Taming the underlying challenges of reliable multihop routing in sensor networks.” ACM SenSys, 14-27.

  3. Levis, P., et al. (2004). “Trickle: A self-regulating algorithm for code propagation and maintenance in wireless sensor networks.” USENIX NSDI, 15-28.

  4. Fasolo, E., et al. (2007). “In-network aggregation techniques for wireless sensor networks: A survey.” IEEE Wireless Communications, 14(2), 70-87.

  5. Gnawali, O., et al. (2009). “Collection tree protocol.” ACM SenSys, 1-14.