Adaptive Topology Optimisation for Scalable and Resilient Industrial IoT Networks

The Industrial Internet-of-Things (IIoT) is a cornerstone of Europe’s digital transformation, enabling real-time sensing and intelligent control across massive interconnected industrial devices for driving efficiency and flexibility in smart manufacturing. However, as IIoT networks scale in size and complexity, they become increasingly vulnerable to device failures and dynamic reconfiguration, thus threatening both production continuity and operational resilience. To address these challenges, this project will deliver a new suite of adaptive and intelligent topology optimisation technologies, advancing the forefront in industrial networking and contributing directly to the EU’s strategic objectives in digital innovation, resilience, and technological autonomy. The project is built on three scientific innovations: 1) to create a novel, compact, and efficient topology representation model capable of capturing the heterogeneity and complexity of real-world IIoT networks, while remaining deployable on resource-constrained industrial edge devices; 2) to develop an original lightweight topology recovery approach that leverages crowd intelligence to maximise network robustness and minimise recovery time in the presence of device failures; 3) to design an innovative AI-powered online topology adjustment mechanism that enhances the agility of large-scale IIoT by accommodating topology changes. The project will also deliver open-source toolkits, datasets, and algorithms to drive community-wide adoption and cross-sector collaboration. The proposed research is ambitious and interdisciplinary, bridging computer networks, AI, and industrial automation. The scientific outcomes will enable European industry to build more robust and autonomous IIoT, setting a new benchmark for industrial connectivity at scale and contributing to the EU’s strategic goals in digital innovation and industrial leadership, reinforcing Europe’s position at the forefront of global smart manufacturing.