Non-Terrestrial Networks represent a valuable solution for providing connectivity to Internet of Things (IoT) devices in remote areas, where classical infrastructure is unavailable. Due to the low-power nature of IoT devices, an Unmanned Aerial Vehicle (UAV) can prevent the energy depletion of these Ground Nodes (GNs) by employing Wireless Power Transfer through an array antenna. Starting from the mathematical modeling of such a scenario, two Mixed-Integer Non-Linear Programming problems are formulated to fairly maximize (i) the energy distribution and (ii) the total amount of data transmitted to a Low Earth Orbit CubeSat. Therefore, it is necessary to optimize the drone kinematics, the transmission scheduling plan, and the beamforming vectors of the array antenna. To cope with their non-convexity, both problems are mathematically manipulated to reach a tractable form, for which two optimization algorithms are proposed and their complexity analyzed. To prove the effectiveness of the overall solution, a comprehensive simulation campaign is conducted under several parameter settings, such as number of GNs and UAV antenna elements with different transmission power levels. Finally, the proposal is compared with a baseline, which confirms the superiority of the proposal up to 7 times in terms of total transmitted data.

In the upcoming Sixth-Generation (6G) of mobile communication systems, space network entities will cooperate with conventional terrestrial networks to provide three-dimensional wireless connectivity around the World. By considering the resulting massive amount of data to be managed into non-terrestrial segments, it will be necessary to dynamically configure functionalities across space network entities. Preliminary contributions in this context focus on quasi-static scenarios, while ignoring the challenging issues (i.e., intermittent visibility, dynamic network configuration, and communication delays) introduced by satellites’ movement and communication protocols enabling the integration of terrestrial and non-terrestrial networks. To bridge this gap, this work presents a network architecture with novel orchestration capabilities of services into non-terrestrial segments. In the proposed approach, the interaction between terrestrial and non-terrestrial entities and the cloud has been detailed across service request, configuration, and provisioning phases. Then, starting from a system model describing the network configuration and the resulting deployment delays of services, an optimization problem has been formulated to dynamically allocate Virtual Network Functions (VNFs) among LEO CubeSats over a looking-ahead horizon, based on service requests, computational capabilities of the involved CubeSats, visibility matrices, and expected deployment delay bounds. Finally, the proposed optimization problem has been solved through three heuristic strategies. Computer simulations have been carried out to demonstrate the ability of the developed strategies to achieve results close to the optimal solution and to ensure better performance against a benchmark scheme.

In the emerging 6G satellite deployments, the interaction between Non-Terrestrial Network terminals and satellite constellations will generate a large surface of attack, which requires the design of novel security architectures. The scientific literature suggests to implement security services as Virtual Network Functions, installed onboard the satellites. The dynamic orchestration of these services, however, still represents a challenging and open research issue. To bridge this gap, this paper presents a novel approach willing to allocate security Virtual Network Functions across satellites, in a dynamic and optimal way. To this end, an optimization problem is formulated by deeply considering the intermittent connectivity between terminals on the Earth and the satellite constellation, the limited computational capabilities of satellites, and the need to provide secure Virtual Network Functions before a given time deadline. Then, the Tabu Search algorithm is used to solve the optimization problem and achieve preliminary results in realistic scenarios. The study illustrates the feasibility of the proposed approach and highlights the issues to address in future research activities.

The Social Internet of Things is gaining momentum thanks to its unique capability of i) autonomously building social relationships among smart objects and ii) supporting the novel services within the Social Network. During the service provisioning, the Trust Management System is in charge of selecting suitable objects able to accomplish the requested services. In this context, available solutions present two relevant issues to be solved. First, they generally assume to select social objects that only achieve higher trustworthiness without considering their actual computing capabilities. Indeed, it would significantly compromise the Quality of Experience in the Social Network of objects. Second, they assume to implement this task directly within constrained devices, becoming unpractical considering their limited computational and storage capabilities. To improve and speed up service provisioning, this paper proposes a novel Trust Management System scheme that fairly distributes service requests by jointly considering the trustworthiness and resource capabilities of available objects. This Trust Management System has been designed to exploit fog computing to efficiently handle the whole process of service provisioning in real-world deployments while relieving constrained devices from all processing and storage efforts. Its behavior is investigated through computer simulations. Obtained results demonstrated that the conceived approach outperforms baseline solutions in terms of latency, fairness in services distribution, and responsiveness in malicious nodes' detection.

The adoption of the Narrowband-Internet of Things technology in satellite communications intends to boost Internet of Things services beyond the boundaries imposed by the current terrestrial infrastructures. Apart from link-level studies in the scientific literature and preliminary 3GPP technical reports, the overall debate is still open. To provide a further step forward in this direction, the work presented herein pursues a novel service-oriented methodology to design an effective solution, meticulously stitched around application requirements and technological constraints. To this end, it conducts link-level and system-level investigations to tune physical transmissions, satellite constellation, and protocol architecture, while ensuring the expected system behavior. To offer a real smart agriculture service operating in Europe, the resulting solution exploits 24 low-Earth orbit satellites, grouped into eight different orbits, moving at an altitude of 500 km. The configured protocol stack supports the transmission of tens of bytes generated at the application layer, by also counteracting the issues introduced by the satellite link. Since each satellite has the whole protocol stack onboard, terminals can transmit data without the need for the feeder link. This ensures communication latencies ranging from 16 to 75 min, depending on the served number of terminals and the physical transmission settings. Moreover, the usage of the early data transmission scheme reduces communication latencies up to 40%. These results pave the way toward the deployment of an effective proof of concept, which drastically reduces the time to market imposed by the current state of the art.

Satellite Communication is expected to play a leading role in 5G & Beyond networks. Current studies, however, focus the attention on physical and link-level aspects, while ignoring to evaluate system-level performance. This paper presents a novel simulation tool, conceived as a new module for the open-source 5G-air-simulator, modeling NB-IoT satellite-based communication systems. Specifically, it implements several link-to-system abstraction models, the cell selection procedure, and a configurable satellite constellation. Furthermore, these essential features are successfully integrated within the rest of the 5G-air-simulator, thus offering the opportunity to test flexible network deployments (e.g., by varying the number and the distribution of users) under different application statistics. To demonstrate the actual effectiveness of the developed tool, this work also presents a preliminary performance assessment of an NB-IoT satellite-based communication system enabling reference monitoring scenarios.