Recent years have seen the proliferation of different techniques for outdoor and, especially, indoor positioning. Still being a field in development, localization is expected to be fully pervasive in the next few years. Although the development of such techniques is driven by the commercialization of location-based services (e.g., navigation), its application to support cellular management is considered to be a key approach for improving its resilience and performance. When different approaches have been defined for integrating location information into the failure management activities, they commonly ignore the increase in the dimensionality of the data as well as their integration into the complete flow of networks failure management. Taking this into account, the present work proposes a complete integrated approach for location-aware failure management, covering the gathering of network and positioning data, the generation of metrics, the reduction in the dimensionality of such data, and the application of inference mechanisms. The proposed scheme is then evaluated by system-level simulation in ultra-dense scenarios, showing the capabilities of the approach to increase the reliability of the supported diagnosis process as well as reducing its computational cost.

Aircrafts fully rely in a wide variety of electronic systems: sensors, navigation equipment, representation screens and communication elements. The interconnection of these avionics implies a huge challenge for the aircraft communication networks. Extremely stringent requirements in terms of reliability and predictability have to be provided for a safe operation. There are also important limitations to recreate those networks in a prototype form, due to the costs of the related equipment and the interest of testing different architectures and possible configurations dynamically. Moreover, performance estimation approaches based solely on network calculus provide limits for worst-case scenarios, without generating a detailed feedback under different circumstances and configurations of the network and different data sources. In this context, the present work proposes and develops an evaluation framework for avionics networks in order to support the verification and validation (V&V) procedures of the communication system before applying for certification. The proposed framework implements an event-based simulator in Simulink for Avionics Full-Duplex Switched Ethernet (AFDX), one of the most extended data protocols for avionics. This is evaluated in comparison with network calculus and bibliography performance estimation approaches, demonstrating its accuracy and capabilities.

It has been long established that crowds generated by social events (e.g., sports matches, parades, fairs...) produce a high impact on cellular network service. However, to estimate such an impact, it is necessary to use data sources classically outside the mobile operator control. In this way, and following a social-aware approach, the forecasting mechanisms should be able to combine both social and network information to obtain reliable predictions. To this end, the present work develops a complete system for its use in the prediction of cellular metrics (e.g., connections, throughput...). The performance of the proposed solution is evaluated in a real cellular network, showing the capabilities of the approach to provide accurate forecasting.

Aircraft are composed of many electronic systems: sensors, displays, navigation equipment, and communication elements. These elements require a reliable interconnection, which is a major challenge for communication networks since high reliability and predictability requirements must be verified for safe operation. In addition, their verification via hardware deployments is limited because these are costly and it is difficult to try different architectures and configurations, thus delaying design and development in this area. Therefore, verification at early stages in the design process is of great importance and must be supported with simulation. In this context, this work presents an event-driven link-level framework and simulator for the validation of avionics networks. The tool presented supports communication protocols commonly used in avionics, such as Avionics Full-Duplex Switched Ethernet (AFDX), as well as Ethernet, which is used with static routing. Also, the simulator provides accurate results by employing realistic models for various devices. The proposed platform was evaluated in the Clean Sky’s Disruptive Cockpit for Large Passenger Aircraft architecture scenario, showing the capabilities of the simulator. Verification speed is a key factor in its application, so the computational cost was analyzed, proving that the execution time is linearly dependent on the number of messages sent and that the increase in the number of nodes has few quadratic components.

The new generation of mobile networks goes beyond classic radio-focus access networks by adopting the softwareisation of functions that typically relied on special-purpose hardware, now to be deployed in as general as possible purpose platforms. The resulting virtualised Radio Access Network (vRAN) follows the Network Function Virtualisation (NFV) paradigm, enabling a distributed and scalable network architecture. However, this approach increases the complexity of management tasks as computing resources now play an essential role in the network provisioning process. In this sense, this work aims to assess the impact of computational resources on the Quality of Experience (QoE) of video streaming services delivered over vRAN-based networks. The obtained results prove that inadequate resource assignment to vRAN instances leads to degradation of the QoE, even if the allocation of radio resources is adequate for the service.

The complexity of cellular networks makes them difficult to manage and prone to failures. This has led to the application of artificial intelligence mechanisms for failure management tasks. Nevertheless, the availability of labeled data on failure cases is limited, making unsupervised techniques the most relevant to apply. However, these techniques require network experts to analyze the results through a costly process to link them to specific cases. Intending to ease the labeling of cases, the present work proposes a framework to determine the relevant metrics for any clustering. Furthermore, the framework is evaluated using data from real cellular networks.