Raspberry Pi-Powered FUDGE Frugal Edge Nodes Aim to Improve the Efficiency of Resource-Limited IoT
Prototype nodes are designed to improve latency, reliability, and performance of IoT deployments where resources are scarce.
Researchers at the Universitat Politécnica de Valéncia and the International Centre for Theoretical Physics (ICTP) have discovered a way to reduce the resource requirements of computing at the edge for the Internet of Things: FUDGE, the frugal edge node.
"The growing connection between the Internet of Things (IoT) and artificial intelligence (AI) poses many challenges that require novel approaches and even a rethinking of the entire communication and processing architecture to meet new requirements for latency, reliability, power consumption and resource usage," the team explains in the paper's abstract. "Edge computing is a promising approach to meet these challenges that can also be beneficial in delivering advanced AI-based IoT solutions in areas where connectivity is scarce and resources are generally limited."
"In this paper, we introduce an edge/fog generic architecture to allow the adoption of edge solutions in IoT deployments in poorly connected and resource limited scenarios. To this end, we integrate, using microservices, an MQTT-based system that can collect ingress data, handle their persistency, and coordinate data integration with the cloud using a specific service called aggregator. The edge stations have a dedicated channel with the aggregator based on LoRa to enable long-range transmissions with low power consumption."
To prove the concept, the team developed a prototype FUDGE node based on a Raspberry Pi 3 Model B+ single-board computer running the Eclipse Mosquitto MQTT broker, InfluxDB, and Docker for container management. The node was used to process environmental sensor data, passed through an aggregator system dubbed a "content proxy" via a novel transport protocol dubbed the LoRa Content Transfer Protocol (LoRaCTP).
The results of testing showed that the proposed approach was robust and performant enough for edge-service deployment, though the team admits that "more work and evaluations are required to completely design all the details." In particular, the researchers are looking at the possibility of switching the current star topology out for a mesh infrastructure to further reduce latency.
The paper has been published under open-access terms as part of the Proceedings of the 1st Workshop on Experiences with the Design and Implementation of Frugal Smart Objects (FRUGALTHINGS'20).