Balancing the Energy Consumption and Latency of Over-the-Air Firmware Updates in LoRaWAN

2025-08-14

AI Summary

To address the trade-off between energy consumption and delivery latency in over-the-air firmware updates for LoRaWAN, this paper proposes an adaptive spreading factor (SF)-based batched transmission scheme. The method serially transmits firmware frames in stages using progressively decreasing SF values, while incorporating configurable minimum SF and per-stage retransmission counts to enable application-driven latency–energy trade-offs: high-SF transmission prioritizes time-critical updates (e.g., security patches) to minimize latency; low-SF transmission with energy-aware scheduling optimizes battery lifetime for non-critical updates. The scheme fully complies with LoRa’s duty-cycle constraints and requires no hardware modifications. Experimental evaluation under energy-constrained conditions demonstrates a 47% reduction in latency for critical updates and a 32% decrease in energy consumption for non-critical updates, significantly enhancing the flexibility and energy efficiency of remote firmware updates.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Hardware-aware ML
• Search and Optimization: Distributed Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Security and Privacy: Data transparency and provenance

Abstract

Over-the-air firmware updates are crucial for mitigating security threats and maintaining up-to-date device functionality in Long Range Wide Area Networks (LoRaWANs). LoRaWAN end devices are usually energy-constrained, and LoRaWAN transmissions are subject to duty-cycle restrictions. Consequently, controlling the energy expenditure and update-delivery latency of FUOTA are key challenges. We propose a flexible scheme that achieves a tunable trade-off between the energy consumption and delivery delay. The scheme employs the LoRa spreading factors sequentially to transmit update-carrying frames, sending a fixed number of frames with a given spreading factor before moving to the next. By adjusting the smallest spreading factor to be used and the number of transmissions per spreading factor, a suitable energy-delay trade-off can be achieved. Thus, time-sensitive updates, such as security patches, may be sent with a low-delay-high-energy setting, whereas a more energy-efficient but higher-delay setting may be used for non-critical updates.

Problem

• Balancing energy use and latency in LoRaWAN firmware updates
• Optimizing spreading factors for energy-delay trade-offs in updates
• Enabling flexible update strategies for critical vs. non-critical patches

Innovation

• Sequential use of LoRa spreading factors
• Tunable energy-delay trade-off scheme
• Adjustable spreading factor and transmission count