Nicola Roberto Zema

COMVIVOR: An Evolutionary Communication Framework Based on Survivors' Devices Reuse

Mobile devices currently available on the market have a plethora of features and enough computing power to make them, at the same time, information consumers, forwarders and producers. Since they are also provided with a set of sensors and usually battery operating, they are perfect candidates to devise a network infrastructure tailored to function during disruptive events. When everything else fails, they could autonomously reorganize and provide to the civilians and rescue teams valuable services and information. In this paper we adapt and enhance a previous designed framework, capable to epidemically diffuse the proper software updates to its nodes, in order to deploy any kind of service as a prompt response to the needs raised in emergency situations. We further propose and integrate a new smart positioning strategy, to speed up the diffusion of software updates by also keeping under control the overall network overhead. The achieved results show the feasibility of our proposal and how the dynamics of diffusion are enhanced by the smart positioning algorithm.

Using UAV-Based Systems to Monitor Air Pollution in Areas with Poor Accessibility

Air pollution monitoring has recently become an issue of utmost importance in our society. Despite the fact that crowdsensing approaches could be an adequate solution for urban areas, they cannot be implemented in rural environments. Instead, deploying a fleet of UAVs could be considered an acceptable alternative. Embracing this approach, this paper proposes the use of UAVs equipped with off-the-shelf sensors to perform air pollution monitoring tasks. These UAVs are guided by our proposed Pollution-driven UAV Control (PdUC) algorithm, which is based on a chemotaxis metaheuristic and a local particle swarm optimization strategy. Together, they allow automatically performing the monitoring of a specified area using UAVs. Experimental results show that, when using PdUC, an implicit priority guides the construction of pollution maps by focusing on areas where the pollutants’ concentration is higher. This way, accurate maps can be constructed in a faster manner when compared to other strategies. The PdUC scheme is compared against various standard mobility models through simulation, showing that it achieves better performance. In particular, it is able to find the most polluted areas with more accuracy and provides a higher coverage within the time bounds defined by the UAV flight time.

Healing Wireless Sensor Networks from Malicious Epidemic Diffusion

Leveraging the concept of controlled node mobility in this paper we develop an algorithm for tracking and controlling proximity malware propagation in Wireless Sensor Networks (WSN). Our proposal aims at: (i) notifying the nodes of malwarepropagation, (ii) leading a flying robot along a path in the WSNthat guarantees the minimum recovery time to (iii) heal the infected nodes. We formulate the targeted curing problem as a binary integer problem and determine the optimal solution by a central solver. We use the analytical result as a benchmark to evaluate the recovery time of the proposed solution. The achieved results show a satisfactory performance in terms of tracking the presence of an ongoing epidemic and healing the nodes.

Using Location Services to Autonomously Drive Flying Mobile Sinks in Wireless Sensor Networks

The use of mobility in a Wireless Sensor Network has already been indicated as a feature whose exploitation would increase the performances and the ease of mantainance in these environments. Expecially in a event-based WSN, where is necessary a prompt response in terms of data processing and offloading, a set of mobile flying sinks could be a good option for the role of autonomous data collectors. For those reasons in this paper we propose a distributed algorithm to independently and autonomously drive a mobile sink through the nodes of a WSN and we show its preferability over more classical routing approaches expecially in the presence of a localized generation of large amount of information. Our result shows that, in the case of fairly complete coverage of the area where the nodes lie, it is possible to promptly notify a mobile sink about the presence of data to offload, drive it to the interested area and achieve interesting performances.

MeDrone: On the use of a medical drone to heal a sensor network infected by a malicious epidemic

The complexity increase in the software and hardware necessary to support more and more advanced applications for Wireless Sensor Networks conspicuously contribute to render them susceptible to security attacks. The nodes of most complex WSN applications sport desktop-level operating systems and this reliance on software make them ideal prey for traditional threats like viruses and general malware. To address these problems, in this paper we devise a system for a mobile node to locate, track, access and cure the infected nodes of a WSN threatened by a proximity malware infection. For this purpose we first devise a curing operation scheme for a dedicated mobile node and then we provide an implementation for it in form of a multiprocess network and movement protocol. In parallel, we provide a mathematical formulation for the aforementioned operation scheme in order to provide an optimized solution. We perform extended simulations putting our proposal against different movement schemes in different network scenarios and we use the results of the mathematical formulation as a benchmark. Furthermore, we introduce a variation of our proposal capable to support the concurrent operation of multiple mobile actors and implement cooperation.

CUSCUS: An integrated simulation architecture for distributed networked control systems

The merging of networking and control fields has always brought interesting innovations but the tools and structures for proper and easy management of experiments still lag behind. Different solutions have been proposed to handle general control problems and, more in detail, for fine control of UAVs (Unmanned Aerial Vehicles) dynamics. They lack, however, an efficient and detailed network-side simulation, usually available only on dedicated software. On the other hand, current advancements in network simulations suites often do not include an accurate simulation of controlled systems. In the middle 2010s, integrated solutions are still lacking. For these reasons, in this paper we propose a simulation architecture for networked control systems. The architecture is based on well-known solutions in both the fields of networking simulation and UAV control simulation. We integrate them into a compact and efficient solution that shows scalability features and negligible architectural delays, as experimental results demonstrate.

A cooperative packet-loss-tolerant algorithm for Wireless Networked Robots rendezvous

This paper studies the effects of an unreliable communication channel on the Wireless Networked Robots (WNR) rendezvous problem. The objective is to drive the robots to keep a desired formation through local exchange of information. A decentralized cooperative packet-loss tolerant algorithm is proposed to guarantee robots rendezvous despite the presence of packet losses. Realistic NS-3 (Network Simulator) simulation results validate the the proposed approach effectiveness.

A GPS-less on-demand mobile sink-assisted data collection in wireless sensor networks

The autonomous data collector is a role recently introduced to improve the performance of Wireless Sensor Networks. When a prompt response for data processing and offloading is necessary, i.e. in the case of event-driven networks, a mobile flying sink could be a good option for that role. In this paper, we introduce FreeFall, a distributed algorithm for the autonomous navigation of a mobile collector through a WSN for on-demand data offloading that does not rely on an absolute coordinate system. We show that, under fairly common circumstances, it is possible to set the trajectory of the mobile sink and fulfill the offloading requests without the needs of additional equipment installed on nodes.We show how our system is preferable over more classical routing solutions especially in the presence of localized generation of large amounts of information.

The CUSCUS simulator for distributed networked control systems: Architecture and use-cases

Abstract The current merging of networking and control research fields within the scope of robotic applications is creating fascinating research and development opportunities. However, the tools for a proper and easy management of experiments still lag behind. Although different solutions have been proposed to simulate and emulate control systems and, more specifically, fleets of Unmanned Aerial Vehicles (UAVs), still they do not include an efficient and detailed network-side simulation, which is usually available only on dedicated software. On the other hand, current advancements in network simulations suites often do not include the possibility to include an accurate description of controlled systems. In the middle 2010s, integrated solutions of networking and control for fleets of UAVs are still lacking. In this paper, we fill such gap by presenting a simulation architecture for networked control systems which is based on two well-known solutions in both the fields of networking simulation (the NS-3 tool) and UAV control simulation (the FL-AIR tool). Three main research contributions are provided: (i) first, we show how the existing tools can be integrated on a closed-loop architecture, so that the network propagation model (NS-3 side) is influenced by the drone mobility and by the 3D scenario map (FL-AIR side); (ii) second, we implement a novel module, which allows modeling realistic 3D environments by importing city-wide characteristics by the popular OpenStreetMap service; (iii) third, we demonstrate the modeling capabilities of the CUSCUS framework on two realistic use-cases, corresponding to well-known application scenarios of UAVs, i.e. dynamic formation control and static coverage of a target area.

A Discretized Approach to Air Pollution Monitoring Using UAV-based Sensing

Recently, Unmanned Aerial Vehicles (UAVs) have become a cheap alternative to sense pollution values in a certain area due to their flexibility and ability to carry small sensing units. In a previous work, we proposed a solution, called Pollution-driven UAV Control (PdUC), to allow UAVs to autonomously trace pollutant sources, and monitor air quality in the surrounding area. However, despite operational, we found that the proposed solution consumed excessive time, especially when considering the battery lifetime of current multi-rotor UAVs. In this paper, we have improved our previously proposed solution by adopting a space discretization technique. Discretization is one of the most efficient mathematical approaches to optimize a system by transforming a continuous domain into its discrete counterpart. The improvement proposed in this paper, called PdUC-Discretized (PdUC-D), consists of an optimization whereby UAVs only move between the central tile positions of a discretized space, avoiding monitoring locations separated by small distances, and whose actual differences in terms of air quality are barely noticeable. We also analyze the impact of varying the tile size on the overall process, showing that smaller tile sizes offer high accuracy at the cost of an increased flight time. Taking into account the obtained results, we consider that a tile size of 100 × 100 meters offers an adequate trade-off between flight time and monitoring accuracy. Experimental results show that PdUC-D drastically reduces the convergence time compared to the original PdUC proposal without loss of accuracy, and it also increases the performance gap with standard mobility patterns such as Spiral and Billiard.