Handling Mobility in Industrial Internet of Things Environments

The Industrial Internet of Things (IIoT) is transforming industrial environments by integrating physical and information systems, enabling advanced functionalities such as real-time monitoring, predictive maintenance, and automated decision-making. To meet the stringent Quality of Service (QoS) requirements in IIoT, including low latency, high reliability, and energy efficiency, robust wireless communication solutions are essential. To this aim, the Internet Engineering Task Force (IETF) developed the 6TiSCH architecture, built upon the IEEE 802.15.4 Time Slotted Channel Hopping (TSCH) access protocol. However, the definition of the 6TiSCH architecture did not take into account the presence of Mobile Nodes (MNs). The mobility management introduces additional challenges, e.g., complex and time consuming join process, desynchronization on node movements, in guaranteeing the QoS requirements. A promising solution to address those challenges is the Synchronized Single-Hop Multi-Gateway (SHMG) architecture, which provides centralized network control by means of a Network Coordinator (NC), enables efficient handovers between Border Routers (BRs) and ensures seamless connectivity for MNs. In this thesis, mobility management within 6TiSCH-based networks is addressed, focusing on SHMG as a key enabler for MNs in IIoT environments. First, solutions to ensure a high network coverage to guarantee the continuity of service are proposed and evaluated. Then, novel scheduling algorithms designed to manage communication resources for MNs are introduced and assessed. Specifically, the Shared Downstream-Dedicated Upstream (SD-DU) scheduling algorithm, designed to ensure that the applications' QoS requirements are met, and the Location-Aware Scheduling Algorithm (LASA) and LASA with Rescheduling (LASA-R), that optimize resource allocation exploiting the knowledge of the location of MNs. Furthermore, a comprehensive analysis and solution set for enhancing mobility management in IIoT networks is provided, extending the research into the Cloud-to-Things Continuum. In this context, the Joint Network and COmputing Resource Allocation (J-NECORA) framework is presented, which optimizes resource allocation across heterogeneous network segments and computing resources. All the solutions presented throughout the thesis are analysed and validated through an ad-hoc simulator, the Mobile6TiSCH simulator, that has been developed based on the OMNeT++ framework.