DeltaIoT: A Real World Exemplar for Self-Adaptive Internet of Things (Artifact)
by M. Usman Iftikhar, Gowri Sankar Ramachandran, Pablo Bollansee, Danny Weyns, and Danny Hughes
The DeltaIoT exemplar enables researchers to evaluate and compare new methods, techniques and tools for self-adaptation in Internet of Things (IoT). The exemplar applies multi-hop communication, where each IoT mote must have a path towards the gateway along other motes. Our motes use LoRa radio technology supporting long range communication. The focus is on dynamically adapting the network settings of the IoT motes (e.g., transmission power and spreading factor) to reduce the energy consumption of the motes and guaranteeing high packet delivery performance, regardless of uncertainties such as sudden changes in traffic load and communication interference. Traditionally, to deal with uncertainties the network settings are either hand-tuned or over-provisioned, resulting in continuous network maintenance. Self-adaptation can automate these tasks. The exemplar provides several reference scenarios for experimentation. DeltaIoT comprises a simulator for offline experimentation and a physical setup of 25 motes that can be accessed remotely for experimentation in the field. This IoT system is deployed at the Computer Science Department Campus of KU Leuven.
Download the DeltaIoT artifact and paper from the Dagstuhl Artifacts Series: