Cornelia-Ionela Badoi

Industrial Internet of Things (IIoT) networks, Microsoft Azure Internet of Things (IoT) Hub, and device twins (DvT) are increasingly recognized as core enablers of adaptive, data-driven manufacturing. This paper proposes a hierarchical IIoT framework that integrates industrial IoT networking, DvT for asset-level virtualisation, system-level digital twins (DT) for cell orchestration, and cloud-native services to support the digital transformation of brownfield, programmable logic controller (PLC)-centric modular automation (MA) environments. Traditional PLC/supervisory control and data acquisition (SCADA) paradigms struggle to meet interoperability, observability, and adaptability requirements at scale, motivating architectures in which DvT and IoT Hub underpin real-time orchestration, virtualisation, and predictive-maintenance workflows. Building on and extending a previously introduced conceptual model, the present work instantiates a multilayered, end-to-end design that combines a federated Message Queuing Telemetry Transport (MQTT) mesh on the on-premises side, a ZigBee-based backup mesh, and a secure bridge to Azure IoT Hub, together with a systematic DvT modelling and orchestration strategy. The methodology is supported by a structured analysis of relevant IIoT and DvT design choices and by a concrete implementation in a nine-cell MA laboratory featuring a robotic arm predictive-maintenance scenario. The resulting framework sustains closed-loop monitoring, anomaly detection, and control under realistic workloads, while providing explicit envelopes for telemetry volume, buffering depth, and latency budgets in edge-cloud integration. Overall, the proposed architecture offers a transferable blueprint for evolving PLC-centric automation toward more adaptive, secure, and scalable IIoT systems and establishes a foundation for future extensions toward full DvT ecosystems, tighter artificial intelligence/machine learning (AI/ML) integration, and fifth/sixth generation (5G/6G) and time-sensitive networking (TSN) support in industrial networks.

This paper presents a solution for a new multidimensional packet classifier of an edge router, based on content - related new fields embedded in the data packets. The technique is applicable to content aware networks. The classification algorithm is using three new packet fields named Virtual Content Aware Network (VCAN), Service Type (STYPE) and U (unicast/multicast) which are part of the Content Awareness Transport Information (CATI) header. A CATI header is inserted into the transmitted data packets at the Service/Content Provider server side, in accordance with the media service definition, and enables the content awareness features at a new overlay Content Aware Network layer. The functionality of the CATI header within the classification process is then analyzed. Two possibilities are considered: the adaptation of the Lucent Bit vector algorithm and, respectively, of the tuple space search, in order to respond to the suggested multi-fields classifier. The results are very promising and can be very useful in the content-aware packet classification.

The paper presents the characteristics of two recently suggested Cognitive Radio (CR) routing protocols, IP Spectrum Aware Geographic (IPSAG) and Head-Cluster IPSAG (HC-IPSAG) protocols, relative to other multi-hop routing protocols. The comparison is guided by specific CR performance criteria, as mobility and spectrum availability awareness. The protocols are representative for different multi-hop routing protocol types. The analysis shows that our protocols respond well to CR demands, especially at high mobility. The results are sustained by statistical results obtained through simulations. However, the price is an increased overhead regarding the control information needed to perform routing.

The paper is about a new routing protocol suggested for Cognitive Radio Networks (CRN) called Head Cluster IP Spectrum Aware Geographic (HC-IPSAG) and the associated performance. The protocol is an extension of the formerly advanced IPSAG routing protocol, for the case of larger CRNs. Splitting of the CRN domain into clusters is considered here. Each cluster is represented by a head node and the inter-cluster routing is done by using the IPSAG routing concepts within the virtual network created by the cluster head nodes. A CRN simulation model has been developed to study the performance of HC-IPSAG. Our results show that the protocol is performing well in the case of high mobility as well as the performance decreases with the growth of the cluster number.

In the recent years Cognitive Radio (CR) technology imposed itself like a very good solution to the increasing spectrum utilization. This technology proposes the development of a new radio type - a cognitive radio - endowed with intelligence that shall sense, share, and use the spectrum opportunities (SOP) of the preexisting wireless networks, that is the channels that are not used by the licensed users. A new routing algorithm for CR networks (CRN): IPSAG - IP Spectrum Aware Geographic based Routing Protocol is presented in the paper. As suggested by the name, the IP hop-by-hop, the geographic, and the spectrum aware routing concepts were used together in the protocol's design. The dynamism and flexibility, characteristic to both CR and IP networks, made us compare the CR concept with the IP concept (a wireless versus wired flexible environment comparison); thus we assumed the IP routing approach for CRN. The proposed strategy is based on hop-by-hop routing, local decisions being taken by nodes according to both local information (CR node's neighborhood) and global information (the entire topology of CRN), channels availability, and destination location.