Christian Vitale

• Doctor of Philosophy
• Reseach Associate at University of Cyprus

With an ever increasing number of unmanned aerial vehicles (UAVs) in flight, there is a pressing need for scalable and dynamic air traffic management solutions that ensure efficient use of the airspace while maintaining safety and avoiding mid-air collisions. To address this need, a novel framework is developed for computing optimized 4D trajectori...

To date, a large body of the literature has looked into the problem of autonomous intersection crossings facilitated by Connected Autonomous Vehicles (CAVs). Nevertheless, existing approaches assume that CAVs know their exact location and system state. This work presents a novel framework that allows for an optimized intersection management, which...

The main goal of the H2020-CARAMEL project is to address the cybersecurity gaps introduced by the new technological domains adopted by modern vehicles applying, among others, advanced Artificial Intelligence and Machine Learning techniques. As a result, CARAMEL enhances the protection against threats related to automated driving, smart charging of...

Multi-access edge computing (MEC) comes with the promise of enabling low-latency applications and of reducing core network load by offloading traffic to edge service instances. Recent standardization efforts, among which the ETSI MEC, have brought about detailed architectures for the MEC. Leveraging the ETSI model, in this paper we first present a...

Current research on robust trajectory planning for autonomous agents aims to mitigate uncertainties arising from disturbances and modeling errors while ensuring guaranteed safety. Existing methods primarily utilize stochastic optimal control techniques with chance constraints to maintain a minimum distance among agents with a guaranteed probability...

Current research on robust trajectory planning for autonomous agents aims to mitigate uncertainties arising from disturbances and modeling errors while ensuring guaranteed safety. Existing methods primarily utilize stochastic optimal control techniques with chance constraints to maintain a minimum distance among agents with a guaranteed probability...

In pursuit of autonomous vehicles, achieving human-like driving behavior is vital. This study introduces adaptive autopilot (AA), a unique framework utilizing constrained-deep reinforcement learning (C-DRL). AA aims to safely emulate human driving to reduce the necessity for driver intervention. Focusing on the car-following scenario, the process i...

Intersection crossing represents one of the most dangerous sections of the road infrastructure and Connected Vehicles (CVs) can serve as a revolutionary solution to the problem. In this work, we present a novel framework that detects preemptively collisions at urban crossroads, exploiting the Multi-access Edge Computing (MEC) platform of 5 G networ...

Intersection crossing represents a bottleneck for transportation systems and Connected Autonomous Vehicles (CAVs) may be the groundbreaking solution to the problem. This work proposes a novel framework, i.e, AVOID-PERIOD, where an Intersection Manager (IM) controls CAVs approaching an intersection in order to maximize intersection capacity while mi...

Road intersections represent the primary bottleneck in transportation systems and connected autonomous vehicles (CAVs) have the potential to aleviate the problem through communication and coordination. As such, this work proposes a novel framework where, accounting for CAVs' location uncertainty, an intersection manager (IM) controls CAVs approachi...

One of the main use cases for advanced cellular networks is represented by massive Internet-of-things (MIoT), i.e., an enormous number of IoT devices that transmit data toward the cellular network infrastructure. To make cellular MIoT a reality, data transfer and control procedures specifically designed for the support of IoT are needed. For this r...

Massive Internet-of-things (MIoT) represents one of the main use cases of 5G, as well as one of the most challenging ones. Accordingly, MIoT traffic is given special treatment in the core network, with the Mobility Management Entity (MME) serving both control and data traffic. In this context, it is critical to properly dimension the MME and to ada...

The paper relates to multi-resource sharing between flows with heterogeneous requirements as arises in networks with wireless links or software routers implementing network function virtualization. Bottleneck max fairness (BMF) is a sharing objective in this context with good performance. The paper shows that BMF results when local fairness is impo...

In this demo, we present a software and hardware platform for designing services in the next generation of wireless networks, in which SDN and SDR are expected to play a key role. We use a LabVIEW-based PXI platform in which LTE-like SISO OFDM PHY Layer is integrated with an open source protocol stack. Such platform can be easily used within an SDN...

This paper tackles the multifaceted challenges of controlling mixed access networks with base stations, access points and D2D relay stations. Mixed access networks are of uncompelling importance since the next generation cellular access networks are envisioned to use different access technologies at once. We propose a unified framework to model thr...

In this paper, we pioneer a novel mechanism that jointly enforces intra-cell and inter-cell resource allocation for future green 5G networks. Our proposal, namely TOMRAN, efficiently coordinates the activity of base stations in small dense cell deployments by means of the ABSF standard tool for inter-cell interference coordination. Additionally, TO...

We consider a queuing system with coupled processors (CPS), in which the service rate at each queue varies over time in function of the set of active queues in the system. Performance analysis of CPS has so far been based on simulations or on complex Markov chains under restricting assumptions on input traffic statistics. In contrast, we propose a...

In this paper we present an analytic approach to performance analysis of ad hoc networks under non saturation conditions, which does not rely on any assumption on traffic statistics. Our approach assumes traffic to be constrained by leaky bucket arrival curves, and it relies on a coupled processors model to capture the dependencies between user ach...

This paper presents a first fully analytical approach to performance evaluation of D2D communication systems, which does not assume the system to be in saturated conditions. We adopt a Coupled Processors model to describe a cellular scenario with D2D users sharing radio resources with cellular users, i.e., adopting in-band underlay D2D schemes. We...

Dense heterogeneous networks constitute the paradigm for the future networks. In fact, recent studies demonstrate that the data traffic demand increases exponentially and the traditional cellular networks are not able to provide enough capacity. For this reason operators and standardisation bodies are particularly eager to solve the problem, hence...

In this paper we present a distributed mechanism based on Principal Component Analysis (PCA) to profile the behavior of the legitimate users in telephone networks. The idea is to take advantage of probes distributed over the network to obtain a compact snapshot of the users they serve. A collector node effectively combines such information to gathe...