This paper proposes a comprehensive framework for optimizing the deployment of Unmanned Aerial Vehicles (UAVs) in a communication system, aiming to minimize the transmission power of UAVs while ensuring the required data rates for ground users. The proposed model accounts for both large- and small-scale fading effects. To accurately capture the characteristics of the wireless channel, the Rician Shadowed fading model is adopted, as it incorporates both line-of-sight (LoS) and nonline-of-sight (NLoS) components. A mathematical formulation of the problem is presented, and the impact of the Rician shadowed fading parameters, the severity of the fluctuations in the LoS component, and the ratio between the powers of the LoS and NLoS components is considered. The simulation results demonstrate that increasing the parameters improves channel conditions, thus reducing the transmission power required to meet the minimum data rate constraints. To address the UAV 3D placement problem, which results in a non-convex and analytically intractable optimization due to the nonlinearities introduced by the channel model. Therefore, we employ a heuristic algorithm, Particle Swarm Optimization Evolutionary (PSO-E).
Electric vehicles are a major step toward sustainable urban mobility. Vehicle-to-Grid (V2G) systems allow energy to be exchanged in both directions between the vehicle and the grid, which makes bi-directional charging possible. For such systems to work reliably and securely, strong communication and protection mechanisms are necessary.Even though several solutions have been suggested in literature, some limitations still exist — such as relying on a trusted third party, using heavy authentication mechanisms, or ignoring the limited capabilities of certain devices. In this work, we propose a solution that follows the ISO 15118 standard, combining blockchain with a lightweight authentication scheme.We used Tamarin Prover for security modeling and RiseV2G for simulation. Our solution meets key security needs — including confidentiality, data integrity, anonymity, and non-repudiation. Results show that it resists many attacks and works well with limited-resource devices, improving performance in terms of computing time, energy use, and network reliability. We also plan to test our system later using IBM Hyperledger Fabric. [1]
The escalating demand for multimedia content requires efficient and scalable distribution solutions for adaptive streaming, particularly MPEG-DASH, in web environments. This paper presents SwarmLayer, a novel hybrid peer-to-peer (P2P) assisted streaming solution designed to enhance web content distribution. SwarmLayer integrates a traditional client-server model with a P2P paradigm, where active users concurrently serve as content distribution nodes by sharing acquired video segments. This approach aims to significantly reduce the load of the origin server, minimize redundant content transmission, and optimize network bandwidth utilization. Implemented as a transparent and non-intrusive intermediate layer between the media player and the content distribution system, SwarmLayer requires no modifications to existing application logic or infrastructure. Its design leverages standard web technologies, including WebRTC for peer connectivity, Service Workers for request interception, and Protocol Buffers for efficient data serialization, along with the MPEG-DASH standard. Experimental evaluations demonstrate substantial server offload, achieving up to a 96% reduction in server traffic, while maintaining seamless playback fluidity across diverse network conditions, including geographically distributed nodes and NAT environments.
This work presents the foundations of a tool created for the simulation and management of airspaces according to the U-space regulations proposed by the European Union for UAV traffic. The tool will provide a realistic simulation of the flight of numerous UAVs in an urban scenario, with the aim of simplifying and reducing the cost of the development and verification process of all the systems involved, as well as anticipating possible conflicts before deploying a solution in the real world. The tool has been built on one of the most advanced physics simulators currently available, Isaac Sim, which offers numerous tools for experiment analysis, allowing multiple tasks to be executed in parallel in a hyper-realistic environment.
The design of effective mobility-aware systems requires a deep understanding of how different user groups navigate and interact within urban environments, enabling the development of services and infrastructures that adapt to dynamic movement patterns. Tourist mobility patterns, in particular, offer valuable insights into the spatial and social dynamics that influence system design decisions for smart cities, recommendation engines, and urban planning applications. This work presents a comprehensive approach to modeling urban mobility networks by examining tourist behavior through network analysis techniques. Using Rome as a case study, we leverage a large dataset of Foursquare check-ins collected over 18 months to construct a co-visitation graph where nodes represent points of interest and edges reflect shared visits by the same users. Through network analysis of Rome’s tourist mobility, our work identifies clear structural differences between visitor types: long-term visitors form cohesive, highly clustered mobility networks, while short-term visitors create more fragmented interaction patterns. Key points of interest (especially transportation hubs and cultural landmarks) serve as essential connectors shaping network flow, following preferential attachment dynamics. Mobility-aware systems play a crucial role in leveraging such insights to design adaptive, data-driven services that respond to varying mobility behaviors, ultimately enhancing urban efficiency and user experience.
