Problem Detection in the Edge of IoT Applications

Abstract

Due to technological advances, Internet of Things (IoT) systems are becoming increasingly complex. They are characterized by being multi-device and geographically distributed, which increases the possibility of errors of different types. In such systems, errors can occur anywhere at any time and fault tolerance becomes an essential characteristic to make them robust and reliable. This paper presents a framework to manage and detect errors and malfunctions of the devices that compose an IoT system. The proposed solution approach takes into account both, simple devices such as sensors or actuators, as well as computationally intensive devices which are distributed geographically. It uses knowledge graphs to model the devices, the system's topology, the software deployed on each device and the relationships between the different elements. The proposed framework retrieves information from log messages and processes this information automatically to detect anomalous situations or malfunctions that may affect the IoT system. This work also presents the ECO ontology to organize the IoT system information.