Towards Large-Scale Material-Integrated Computing: Self-Adaptive Materials and Agents

In the past decades there was an exponential growth of computer networks and computing devices, connecting computers with a size in the m3 range. The Internet-of-Things (IoT) emerges connecting everything, demanding for new distributed computing and communication approaches. Currently, the IoT connects devices with a size in the cm3 range. But new technologies enable the integration of computing in materials and technical structures with sensor and actor networks connecting devices in the mm3 range. This work investigates issues in large-scale computer networks related to the deployment of low- and very-low resource miniaturized nodes integrated within materials. These networks operate under harsh conditions with possibility of technical failures requiring robustness. Despite sensor networks used for structural monitoring, self-adaptive materials can profit from self-organizing and autonomous distributed data processing using Multi-agent systems, demonstrated in this paper. Self-adaptive materials are able to adapt the material or mechanical structure properties based on their environmental interaction (load/stress) to minimize the risk of overloading. A structure that could change its local properties in service based on the identified loading situation could thus potentially raise additional weight saving potentials and thus supporting lightweight design, and in consequence, sustainability.