Dear Nordic,
We’re working on a Smart Door Lock project built on custom hardware that includes an nRF5340 and several other controllers. For firmware updates, we’ve adopted Nordic’s Matter OTA mechanism, with some customizations. Specifically, we modified the DFU target library and the CBOR-based multi-image bundling process to package all controller firmware — including the nRF5340’s application and network core images — into a single combined Matter OTA binary (size approx. 3.3 MBs).
This unified OTA image is then passed to the Matter OTA provider (using chip-tool or eco-system) for delivery to the OTA requestor — the smart lock device running on our Nordic-based hardware. Using the setup, we’ve successfully transferred the complete Matter OTA image from the OTA provider to the OTA requestor device. All controllers, including the Nordic cores and external controllers, were able to update and switch to the newly transferred image without issues.
We are currently facing an issue with time of Matter OTA firmware update over Thread. Specifically, transferring a 3.3 MB firmware image (approximately 3400 OTA packets, assuming a 1024-byte block size) is taking around 25–30 minutes, which seems excessively long.
Given the capabilities of the Thread protocol, we expected this transfer to complete much faster — especially since, in theory, Thread can handle around 500 KB per minute under normal conditions. We understand that protocol overhead (such as BDX, Secure CoAP, and UDP headers) contributes to some reduction in effective throughput. However, even with that accounted for, the current transfer duration is far from optimal.
Could you guide us on how we can significantly reduce the image transfer time over Matter (using OpenThread)? What strategies or optimizations can be applied to improve both the reliability and speed of the OTA process?
Also, would reducing the poll period (using otLinkGetPollPeriod() / otLinkSetPollPeriod()) help accelerate the image transfer, particularly in sleepy end devices?
Thanks & Regards
Kaushik Parsana
