Deep Sleep For Mesh Repeaters: Power Saving Strategies

Hey guys,

Let's dive into an interesting discussion about optimizing power consumption in mesh networks, specifically focusing on repeaters. The core idea here is to explore the possibility of putting repeaters into a deep sleep mode for the majority of the time, waking them up only when necessary. This strategy could significantly extend the battery life of these devices, making mesh networks more practical for various applications, especially those relying on battery power. Let's break down the concept, the potential benefits, and the challenges we might face.

The Core Concept: Deep Sleep for Power Efficiency

The primary concept revolves around leveraging the deep sleep mode in repeaters to conserve power. Repeaters, by nature, are designed to be always-on devices, constantly listening for and relaying signals within the mesh network. This continuous operation, however, can be quite power-intensive. By introducing a deep sleep mode, we allow the repeater to enter a state of very low power consumption for extended periods. Think of it like putting your phone on airplane mode; it's still on, but it's using minimal energy.

The magic happens in the way we wake up these sleeping beauties. There are a couple of primary mechanisms we can consider:

• Periodic Wake-ups for Advertisements: The repeater can wake up at regular intervals to broadcast advertisement signals. These signals essentially say, "Hey, I'm here and ready to relay messages!" This allows other nodes in the network to discover the repeater and establish communication paths. The frequency of these wake-ups can be adjusted based on the network's needs and the desired power savings.
• Wake-on-LoRa Packets: This approach involves the repeater listening for specific LoRa packets that act as wake-up calls. When such a packet is received, the repeater springs back to life and processes the incoming data. This method can be more efficient than periodic wake-ups, as the repeater only wakes up when there's actual traffic to handle.

Now, you might be wondering, what's the big deal? Let's look at the potential power savings.

Potential Power Savings: A Real-World Example

To illustrate the potential benefits, let's consider a specific example. According to the initial post, a Heltec v3 repeater can see a significant drop in power consumption when it enters deep sleep mode – from around 5mA down to a mere 1mA. That's a fivefold reduction in power usage! For devices running on batteries, this difference can translate into a substantial increase in operational lifespan. Imagine a sensor node that can now operate for months or even years on a single battery charge, thanks to this power-saving technique.

Similar gains can be expected with other microcontroller units (MCUs), such as those based on the NRF series. These MCUs are also known for their low-power capabilities, and deep sleep modes can further enhance their energy efficiency.

Visualizing the Impact

The included image visually highlights the potential power savings. The difference between active mode and deep sleep mode is stark, showcasing the potential for significant energy conservation.

The Trade-Offs: Potential Challenges and Considerations

Of course, with any optimization strategy, there are trade-offs to consider. The deep sleep approach is no exception. The primary concern here is the potential for missed packets.

Packet Loss and Retries

When a repeater is in deep sleep, it's essentially deaf to the network. It won't hear any incoming packets during this period. This means that some packets might be missed if they arrive while the repeater is snoozing. However, this isn't necessarily a deal-breaker. Mesh networks are designed to be resilient, and they often incorporate mechanisms for handling packet loss.

One common technique is to use retries. If a node doesn't receive an acknowledgment for a transmitted packet, it will simply try sending it again. The repeater, upon waking up, will then process these retried packets. This approach adds a layer of reliability, ensuring that important data eventually gets through.

However, excessive retries can also consume power and increase latency. Therefore, it's crucial to strike a balance between power savings and network performance. Factors like the wake-up interval and the retry strategy need to be carefully tuned to optimize the overall system behavior.

Synchronization and Timing

Another challenge lies in synchronizing the sleep cycles of multiple repeaters within the network. If repeaters wake up and go to sleep at the same time, there could be periods of reduced network coverage. To mitigate this, it might be necessary to implement some form of sleep cycle staggering or randomization. This would ensure that there's always a sufficient number of active repeaters available to relay messages.

Network Topology and Dynamics

The effectiveness of deep sleep also depends on the network topology and how frequently nodes move or change their communication patterns. In a highly dynamic network, where nodes are constantly joining, leaving, or changing routes, the deep sleep approach might be less effective. More frequent wake-ups might be needed to maintain connectivity and adapt to the changing network conditions.

Key Questions and Considerations for Implementation

So, where do we go from here? Let's outline some key questions and considerations that need to be addressed before implementing deep sleep for repeaters.

• Wake-Up Interval: How frequently should the repeaters wake up to send advertisements or listen for packets? This is a critical parameter that affects both power consumption and network responsiveness. Shorter intervals mean lower latency but higher power consumption, and vice versa.
• Wake-Up Mechanism: Should we rely on periodic wake-ups, wake-on-LoRa packets, or a combination of both? The choice depends on the specific application requirements and the network's traffic patterns. Wake-on-LoRa can be more efficient for sporadic traffic, while periodic wake-ups might be better for networks with more consistent activity.
• Retry Strategy: How many retries should be allowed for lost packets? A higher number of retries improves reliability but also increases power consumption and latency. We need to find the sweet spot that balances these factors.
• Synchronization: How can we ensure that repeaters don't all sleep at the same time? Sleep cycle staggering or randomization techniques can help maintain network coverage.
• Network Monitoring: How can we monitor the network's performance and adapt the deep sleep parameters as needed? Real-time monitoring and adaptive algorithms can optimize power savings while ensuring reliable communication.
• Hardware and Software Support: What hardware and software modifications are needed to implement deep sleep? This might involve changes to the firmware, the radio configuration, and the power management circuitry.

Next Steps: Experimentation and Prototyping

The next logical step is to put these ideas into practice through experimentation and prototyping. We can start by:

• Setting up a test network: Deploy a small-scale mesh network with a few repeaters and sensor nodes.
• Implementing deep sleep: Modify the repeater firmware to incorporate deep sleep functionality.
• Measuring power consumption: Use appropriate measurement tools to quantify the power savings achieved with deep sleep.
• Evaluating network performance: Assess the impact of deep sleep on packet loss, latency, and overall network reliability.
• Tuning parameters: Experiment with different wake-up intervals, retry strategies, and synchronization techniques to optimize the system.

By gathering empirical data, we can gain valuable insights into the effectiveness of deep sleep and refine our approach for real-world deployments.

Conclusion: A Promising Path to Power Efficiency

In conclusion, the idea of using deep sleep for mesh repeaters holds significant promise for improving power efficiency. By allowing repeaters to spend most of their time in a low-power state, we can potentially extend battery life and make mesh networks more practical for a wider range of applications. While there are challenges to overcome, such as packet loss and synchronization, these can be addressed through careful design and optimization. With further research, experimentation, and collaboration, we can unlock the full potential of deep sleep and create more energy-efficient and sustainable mesh networks. So, what are your thoughts on this, guys? Let's keep the discussion going and explore the best ways to bring this concept to life!