The Polling Pattern in Embedded Systems

Introduction

In many embedded systems, it’s not always possible — or practical — to use interrupts. Some peripherals don’t provide interrupt lines, others generate events too frequently to handle efficiently, and certain safety-critical systems prefer deterministic control loops over asynchronous behavior.

In these cases, the Polling Pattern offers a simple, predictable way to monitor sensors and hardware states. Rather than reacting to interrupts, the system periodically checks the hardware status at a defined interval.

Polling is especially common in:

• Periodic sensor sampling (e.g., temperature, pressure, battery voltage).
• Systems with limited or noisy interrupt lines.
• Deterministic control loops (e.g., motor control, PID systems).
• Safety-critical logic that must always check specific conditions in a known order.

While interrupts favor reactivity and energy savings, polling favors predictability and simplicity — particularly when the system has strict timing constraints or limited interrupt capabilities.

What is the Polling Pattern?

The Polling Pattern is a structured approach to periodically reading sensors, checking device status, or scanning inputs. It defines:

1. A polling schedule — when and how often to check each source.
2. A loop or timer that drives these checks at fixed or variable intervals.
3. A state or change detector that only triggers actions when values change or cross thresholds.

This prevents unnecessary processing and ensures consistent timing behavior across all sensors or inputs.

Core responsibilities

1. Timing control – determine polling frequency (fixed or adaptive).
2. Event detection – recognize meaningful changes or thresholds.
3. Load balancing – distribute polling load over time.
4. Power management – combine polling with sleep modes to minimize CPU activity.
5. Error detection – detect missing data or stuck sensors.

When to Use It

Use the Polling Pattern when:

• Interrupts are unavailable, noisy, or shared across multiple peripherals.
• Deterministic timing and order of operations are required.
• Data changes slowly (e.g., temperature, battery voltage, humidity).
• The system already has a main loop that runs regularly (superloop architecture).
• Interrupt overhead would outweigh its benefits (e.g., very high-frequency signals).

Avoid pure polling when:

• Precise timing or low latency is required.
• Power must be minimized with long sleep periods.
• Multiple asynchronous events compete for CPU attention.

Benefits

Predictable timing – system knows exactly when each input is checked.
Simplified concurrency – no interrupt contention or reentrancy issues.
Easier debugging – flow is deterministic and linear.
No need for ISR-safe code – all logic runs in one context.
Useful for slow or steady sensors – avoids ISR overhead.

Drawbacks

Higher CPU load – especially if polling too frequently.
Higher latency – events are only seen on the next poll cycle.
Energy cost – CPU can’t stay in deep sleep for long.
Scalability – as more devices are added, timing gets harder to manage.

Design Variants

1. Fixed-Interval Polling (Simple Superloop)

A fixed-frequency loop checks all sensors or devices in sequence.

• Use Case: Small systems with predictable workloads.
• Pros: Deterministic, simple to implement.
• Cons: Wastes cycles if sensors rarely change.

2. Staggered or Round-Robin Polling

Distribute polling load across multiple cycles so not all devices are read every iteration.

• Use Case: Many slow sensors; CPU load balancing.
• Pros: Smooths CPU usage.
• Cons: Slightly more complex scheduler.

3. Adaptive Polling

Adjust polling rate based on conditions — slower when stable, faster when changes are detected.

• Use Case: Battery-powered IoT sensors.
• Pros: Energy efficient, responsive to activity.
• Cons: Requires feedback mechanism and hysteresis.

4. Event-Triggered Polling (Hybrid Pattern)

Poll frequently after an event, then slow down again. Often used when interrupts are unreliable or limited.

• Use Case: Motion-triggered sensor sampling.
• Pros: Combines interrupt and polling benefits.
• Cons: More logic to manage state transitions.

5. Multi-Rate Polling Scheduler

Each sensor or subsystem has its own poll rate (e.g., 1 ms for encoder, 100 ms for temperature). Scheduler triggers them individually.

• Use Case: Mixed-rate systems (industrial control, robotics).
• Pros: Efficient, flexible.
• Cons: Requires small scheduler or timing manager.

Concurrency & Timing Rules

• Avoid long operations inside the polling loop.
• Use precise timers or tick counters for stable timing (don’t rely on loop speed).
• Decouple data acquisition and processing (sample first, process later).
• Log last poll times to detect missed intervals.
• Integrate power management — allow idle or sleep between poll cycles.

Example — Fixed-Interval Polling Loop (Bare Metal)

#include <stdint.h>
#include <stdbool.h>
#include <stdio.h>

extern uint32_t millis(void);     // System uptime in ms
extern int read_temperature(void);
extern int read_light_sensor(void);

#define POLL_INTERVAL_MS 1000

int main(void) {
    uint32_t last_poll = 0;

    while (1) {
        uint32_t now = millis();

        if ((now - last_poll) >= POLL_INTERVAL_MS) {
            last_poll = now;

            int temp = read_temperature();
            int light = read_light_sensor();

            printf("Temp: %d°C, Light: %d lx\n", temp, light);

            // React to significant changes only
            if (temp > 50) handle_overheat();
            if (light < 10) enable_backlight();
        }

        // Optional sleep between polls
        power_sleep_until_next_tick();
    }
}

Example — Multi-Rate Polling Scheduler (FreeRTOS)

#include "FreeRTOS.h"
#include "task.h"
#include <stdio.h>

static void temperatureTask(void *pv) {
    for (;;) {
        int t = read_temperature();
        printf("Temperature: %d\n", t);
        vTaskDelay(pdMS_TO_TICKS(1000)); // 1 Hz
    }
}

static void batteryTask(void *pv) {
    for (;;) {
        int v = read_battery_voltage();
        printf("Battery: %d mV\n", v);
        vTaskDelay(pdMS_TO_TICKS(5000)); // 0.2 Hz
    }
}

int main(void) {
    xTaskCreate(temperatureTask, "Temp", 512, NULL, 1, NULL);
    xTaskCreate(batteryTask, "Battery", 512, NULL, 1, NULL);
    vTaskStartScheduler();
}

Each task polls its respective input at its own rate. The scheduler ensures accurate timing without blocking other tasks.

Power Considerations

Polling can be power-hungry if done carelessly. To optimize:

• Increase poll intervals when data changes slowly.
• Batch readings — poll several sensors together, then sleep.
• Use low-power timers to wake CPU precisely at polling intervals.
• Use adaptive or event-triggered polling to adjust rates dynamically.
• Combine polling with the Interrupt Pattern for hybrid control (e.g., interrupt wakes CPU → short polling window → back to sleep).

Testing & Debugging

• Verify that poll intervals match requirements — use oscilloscopes or logic analyzers for timing validation.
• Simulate noisy signals to check that polling doesn’t miss transient changes.
• Measure CPU duty cycle and adjust poll intervals for power optimization.
• Log time between polls to ensure scheduler drift doesn’t accumulate.
• Test priority between multiple polling loops to prevent starvation.

Anti-Patterns

• Polling at extremely high rates without purpose (CPU starvation).
• Using blocking delays (delay_ms()) instead of proper tick-based logic.
• Mixing unrelated work in polling loop.
• Neglecting missed data or sampling jitter.
• Polling hardware that provides interrupts (wastes CPU).

Comparison: Polling vs Interrupts

Best Practices & Checklist

• Use non-blocking timing (tick counters, RTOS delays).
• Align poll intervals with sensor response time.
• Group related sensors to reduce overhead.
• Avoid jitter by using stable clock references.
• Combine polling with interrupts for hybrid efficiency.
• Log missed polls or overruns.
• Optimize sleep cycles between polls for energy savings.

Conclusion

The Polling Pattern remains one of the most reliable and transparent techniques in embedded systems. It offers deterministic timing, simplicity, and control — making it indispensable for certain classes of systems like control loops, low-end MCUs, or safety-critical modules.

While interrupts enable fast reactions and energy savings, polling excels in predictability and stability. In many real-world designs, the two coexist: interrupts wake the system, while polling validates and processes data in a controlled loop.

By thoughtfully combining the Polling Pattern with Interrupt, Observer, or Mediator patterns, engineers can build embedded systems that balance responsiveness, reliability, and energy efficiency.