Enabling Edge processing on LoRaWAN architecture

TL;DR

This work addresses the scalability and latency challenges of LoRaWAN by introducing Edge2LoRa, an edge-processing extension that integrates with the OTAA-based architecture while preserving security and backward compatibility. Edge2LoRa adds per-ED edge gateways (E2GWs) and a group-key framework backed by elliptic-curve cryptography to enable secure local data processing and aggregation before forwarding to the Application Server. The approach improves latency, reduces uplink bandwidth, and enhances scalability and privacy by processing data at the edge and limiting exposure to the central cloud. The demonstrated results show substantial reductions in latency and network traffic, validating the practicality and security of edge-enabled LoRaWAN deployments for large-scale IoT systems.

Abstract

LoRaWAN is a wireless technology that enables high-density deployments of IoT devices. Designed for Low Power Wide Area Networks (LPWAN), LoRaWAN employs large cells to service a potentially extremely high number of devices. The technology enforces a centralized architecture, directing all data generated by the devices to a single network server for data processing. End-to-end encryption is used to guarantee the confidentiality and security of data. In this demo, we present \edgelora, a system architecture designed to incorporate edge processing in LoRaWAN without compromising security and confidentiality of data. \edgelora maintains backward compatibility and addresses scalability issues arising from handling large amounts of data sourced from a diverse range of devices. The demo provides evidence on the advantages in terms of reduced latency, lower network bandwidth requirements, higher scalability, and improved security and privacy resulting from the application of the Edge processing paradigm to LoRaWAN.

Figures (2)

• Figure 1: Demo hardware architecture.
• Figure 2: Edge2LoRa flow diagram.