238  Multi-Hop Ad Hoc: Assessment and Practice

238.1 Learning Objectives

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

  • Evaluate Multi-Hop Designs: Test understanding through knowledge check questions
  • Avoid Common Pitfalls: Recognize and prevent typical multi-hop deployment mistakes
  • Apply Best Practices: Use lessons learned from real-world implementations
  • Connect Concepts: Navigate to related topics for deeper learning

238.2 Prerequisites

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

238.3 Knowledge Check

Question: What is the primary advantage of multi-hop communication in WSN?

Explanation: B. Multi-hop relays messages through intermediate nodes, extending coverage beyond the radio range of any single node.

Question: How does increasing hop count typically affect communication?

Explanation: B. Each hop adds delay and is another potential failure point, increasing end-to-end latency and the chance of packet loss.

Question: In multi-hop WSN, which nodes typically consume the most energy?

Explanation: B. Nodes nearer the sink relay traffic for many sources (“funnel effect”), so their transmit/receive duty cycle is higher and batteries drain faster.

Question: Which class of ad hoc routing protocols discovers routes only when data needs to be sent (instead of maintaining full tables continuously)?

Explanation: Reactive protocols (e.g., DSR/AODV) perform route discovery on demand, reducing periodic control overhead when communication is sparse.

Question: What is typically considered the optimal range for hop count in multi-hop IoT networks?

Explanation: C. The 3-5 hop range typically offers the best balance between range extension and maintaining acceptable latency and reliability. Beyond 5 hops, complexity and failure probability often outweigh coverage benefits.

Question: When should you choose single-hop over multi-hop networking?

Explanation: D. Single-hop is preferred for compact deployments where all nodes can reach the gateway directly and where simplicity and low latency are important.

238.4 Common Misconceptions

ImportantCommon Misconceptions

Misconception 1: “More hops always means better coverage”

  • Reality: While multi-hop extends range, each hop adds latency and potential failure points. The optimal hop count balances coverage extension with reliability and latency requirements.

Misconception 2: “Ad hoc networks don’t need any planning”

  • Reality: Though self-organizing, ad hoc networks still require careful design of node density, transmission power, routing protocols, and energy management strategies.

Misconception 3: “All nodes in ad hoc networks consume equal energy”

  • Reality: Nodes near the sink create a “funnel effect” - they relay traffic from many sources and deplete batteries much faster than edge nodes.

Misconception 4: “Multi-hop is always more energy-efficient than long-range transmission”

  • Reality: This depends on the scenario. While individual hops use less power, the total network energy (summed across all relay nodes) may exceed direct long-range transmission for certain distances.

238.5 Common Pitfalls

CautionPitfall: Ignoring the Energy Hole Problem

The mistake: Deploying multi-hop sensor networks with uniform battery capacity across all nodes, then discovering that nodes closest to the gateway die within weeks while edge nodes still have 80% battery.

Why it happens: Network designers calculate average energy consumption without modeling the “funnel effect” - nodes near the sink relay traffic from all upstream nodes. A node 1 hop from the gateway may forward 50x more packets than edge sensors.

The fix: Use heterogeneous deployment - nodes near the sink should have larger batteries (2-4x capacity), solar/mains power, or be designated as upgradable relay stations. Alternatively, deploy multiple sinks to distribute the traffic load, or implement load-balancing routing that spreads relay duties across multiple paths.

CautionPitfall: Exceeding the Practical Hop Limit

The mistake: Designing networks with 8-10+ hops to maximize coverage, then experiencing 40%+ packet loss and multi-second latencies that render the system unusable.

Why it happens: Each hop has independent failure probability. With 95% per-hop reliability (good for wireless), a 10-hop path delivers only 60% of packets (0.95^10 = 0.60). Latency accumulates linearly, but reliability degrades exponentially.

The fix: Limit designs to 3-5 hops maximum for reliable operation. For larger coverage areas, deploy additional gateways/sinks rather than extending hop count. If more hops are unavoidable, implement acknowledgments and retransmissions at every hop (not just end-to-end), and use link quality metrics to avoid marginal links.

CautionPitfall: Assuming Symmetric Links

The mistake: Building routing tables based on received signal strength (RSSI) from neighbors, assuming that if node A can hear node B clearly, then B can also hear A equally well.

Why it happens: Radio propagation is often asymmetric due to antenna orientation, local interference sources, transmit power differences, and environmental obstacles. Node A’s transmission may take a different physical path than node B’s response.

The fix: Validate links bidirectionally before adding to routing tables. Use bidirectional link probing: node A sends probe, node B responds, and A confirms receipt. Measure link quality in both directions separately. Avoid routes using unidirectional links - they cause ACK failures and route discovery loops. Consider using ETX (Expected Transmission Count) which inherently measures both directions.

CautionPitfall: Ignoring Duty Cycle Impact

The mistake: Designing multi-hop routing assuming all nodes are always awake and ready to forward packets.

Why it happens: Energy-constrained IoT nodes use duty cycling (sleeping 90-99% of the time). A packet arriving at a sleeping relay node either waits (adding latency) or is dropped (reducing reliability).

The fix: Use synchronous duty cycling protocols where neighbors coordinate wake schedules, or asynchronous protocols with low-power listening. Factor wake-up latency into end-to-end timing calculations. Consider wake-on-radio capabilities for time-critical applications.

238.6 Best Practices Summary

TipMulti-Hop Network Design Best Practices

Planning Phase:

  1. Survey the deployment area - Measure actual radio range with representative hardware, not theoretical maximum
  2. Calculate hop count - Target 3-5 hops maximum; add gateways if more coverage needed
  3. Identify funnel points - Mark locations where traffic concentrates; plan for larger batteries or power sources

Deployment Phase:

  1. Test links bidirectionally - Verify both directions of every link before including in routing tables
  2. Use heterogeneous nodes - Relay-heavy positions get larger batteries, solar panels, or mains power
  3. Deploy incrementally - Validate each section works before expanding coverage

Operation Phase:

  1. Monitor energy distribution - Track which nodes drain fastest; reposition or replace proactively
  2. Log packet loss by path - Identify weak links before complete failure
  3. Plan for graceful degradation - Design so losing one relay affects minimal sensors

238.9 Summary

This chapter covered assessment and best practices for multi-hop networks:

  • Knowledge Checks: Six questions testing understanding of multi-hop benefits, hop count impacts, energy distribution, routing protocols, and design decisions
  • Common Misconceptions: Clarified four false assumptions about coverage, planning, energy, and efficiency
  • Critical Pitfalls: Identified four major deployment mistakes - energy hole problem, hop limit violations, asymmetric link assumptions, and duty cycle oversight
  • Best Practices: Nine guidelines organized across planning, deployment, and operation phases
  • Cross-References: Links to related topics in ad hoc routing, WSN, and interactive learning resources

238.10 What’s Next

Return to Multi-Hop Fundamentals for an overview, or continue exploring other IoT architecture topics such as edge computing, fog computing, or software-defined networking to understand different approaches for organizing and managing IoT deployments.