National Projects

ONOFRE-4-UPCT (Multi-stakeholder Network Planning and Orchestration for Reliable and Secure Connected Mobility: Multi-RAT Planning and Operation) is the subproject of the ONOFRE-4 collaborative project that will be carried out by Universidad Politécnica de Cartagena. ONOFRE-4 aims to develop efficient planning and management mechanisms for network infrastructures equipped with computing resources. The focus is on providing support for connected, reliable and secure mobility, with special consideration given to the interrelation between networks operated by different actors. The ONOFRE-4-UPCT subproject will focus on novel methods and algorithms for multi-RAT operation and planning of networks shared by multiple stakeholders. Multi-RAT capabilities will be enhanced by multichannel operation, and low power technologies will be considered to cover the requirements of vulnerable road users (VRU) specific devices. P2MP coherent pluggable transceivers, coupled with a hierarchical SDN controller as orchestrator will be used to satisfy constraints at the core network. Both classical methods and ML techniques will be exploited and integrated in constrained devices for real experiments and simulation tools. A mobile crowdsensing scenario with VRU-specific technologies will be used to test effective multistakeholder operation and cooperation over heterogeneous links. UPCT will leverage the Cartagena City Council air monitoring networks, OBUs developed in previous projects and the UMU Gaia 5G lab for these real tests. UPCT will lead WP3 (Wireless infrastructures: Planning and Operation of Multi-RAT Networks), and it will also participate on WP1 (Design of Reference Scenarios and System Architecture), WP2 (Wired Infrastructures: Planning and Operation of Optical Networks) and WP5 (Integration, Testing and Validation) on the final integration of ONOFRE-4 project. In any case, the collaborative project has been conceived as an integrated project and most tasks involve multi-partner collaboration at different levels.

The MovIoT proof-of-concept proposes the prototyping of an environmental monitoring solution consisting of a necessary and significant number of measurement units for e-scooters equipped with sensorisation and IoT communications, and a set of data processing software modules.

The WILLIOT project proposes a simulation framework using ray-tracing for LPWAN, 5G and beyond 5G (B5G) networks if the field of mobile IoT, which will provide accurate performance indicators under different network configuration parameters and variable reference scenarios. Simulation results will be extracted from modelled scenarios and compared with real measurements taken for a real LoRaWAN/5G deployment based on connected personal mobility vehicles. This will involve a mobile IoT scenario covering a broad area with diverse connectivity locations.

The project ONOFRE-3 deals with a 5G/6G ecosystem featured by the heterogeneity of the edge, fog, and cloud processing layers for proper management of dynamic QoS application requirements running on mobile nodes. To overcome this complexity, AI and Machine Learning techniques for contextual information prediction and network management are proposed. AI/ML can also support both offline planning methods and multiaccess coordination and control and be deployed at end devices. In this scenario, security is also mandatory from the start, hence, advanced cloud data privacy and security techniques are proposed to be smoothly managed and controlled across different cloud computing domains. Finally, practical evaluation of these mechanisms needs a realistic application scenario with clear requirements. In this line, CCAM and C-ITS verticals are taken for reference evaluation, which provide clearly defined and demanding QoS requirements and serve as reference area to analyse and develop concrete and meaningful benchmarks in a massive latency-bounded slice.

MECANO aims at Improving urban mobility in terms of efficiency and carbon footprint, by using sustainable transport means interconnected as IoT nodes and infrastructure sensors to gather pollution and traffic data.

The Go2Edge Network is a multidisciplinary team of 15 entities that aims to combine the experience of these entities, coordinating research efforts and sharing results on technologies that bring computing and storage resources closer to the edge of the network. To this end, a multidisciplinary vision is developed with complementary capacities and interests diverse in the technologies involved in the work scenario: (i) distributed computing, (ii) cloud and fog computing, (iii) communications networks, (iv) cyber security and (v) end applications allowing to exploit these technologies.