DingNet: A Self-Adaptive Internet-of-Things Exemplar
Recent efforts have shown that research on self-adaptive systems can benefit from exemplar to evaluate and compare new methods, techniques and tools. One highly relevant application domain for self-adaptation is the Internet-of-Things (IoT). While some initial exemplars have been proposed for IoT, these applications are small in scale and hence limited to support research on larger IoT deployments, such as typically required in smart cities. To address this limitation, we introduce the DingNet exemplar, a reference implementation for research on self-adaptation in the domain of IoT. DingNet offers a simulator that maps directly to a physical IoT system that is deployed in the area of Leuven, Belgium. DingNet models a set of geographically distributed gateways that are connected to a user application deployed at a front-end server. The gateways can interact over a LoRaWAN network with local, possibly mobile motes that can be equipped with sensors and actuators. The exemplar comes with a set of scenarios for comparing the effectiveness of different self-adaptive solutions. We illustrate how the exemplar is used for a typical adaptation problem of IoT where mobile motes dynamically adapt their communication settings to ensure reliable and energy efficient communication.