FUDGE: a frugal edge node for advanced IoT solutions in contexts with limited resources

Abstract

[EN] The growing connection between the Internet of Things (IoT) andArtificial Intelligence (AI) poses many challenges that require novelapproaches and even a rethinking of the entire communicationand processing architecture to meet new requirements for latency, reliability, power consumption and resource usage. Edge computingis a promising approach to meet these challenges that can also bebeneficial in delivering advanced AI-based IoT solutions in areaswhere connectivity is scarce and resources are generally limited.In this paper, we introduce an edge/fog generic architecture toallow the adoption of edge solutions in IoT deployments in poorlyconnected and resource limited scenarios. To this end, we integrate,using microservices, an MQTT based system that can collect ingressdata, handle their persistency, and coordinate data integration withthe cloud using a specific service calledaggregator. The edge stations have a dedicated channel with the aggregator based on LoRa to enable long-range transmissions with low power consumption. Some details of the implementation aspects are described along withsome preliminary results. Initial testing of the architecture indicatesthat it is flexible and robust enough to become an alternative forthe deployment of advanced IoT services in resource-constrainedcontexts.