Angelo Trotta

Self-organizing aerial mesh networks for emergency communication

Guaranteeing network connectivity in post-disaster scenarios is challenging yet crucial to save human lives and to coordinate the operations of first responders. In this paper, we investigate the utilization of low-altitude aerial mesh networks composed by Small Unmanned Aerial Vehicles (SUAVs) in order to re-enstablish connectivity among isolated end-user (EU) devices located on the ground. Aerial ad-hoc networks provide the advantage to be deployable also on critical scenarios where terrestrial mobile devices might not operate, however their implementation is challenging from the point of view of mobility management and of coverage lifetime. In this paper, we address both these issues with three novel research contributions. First, we propose a distributed mobility algorithm, based on the virtual spring model, through which the SUAV-based mesh node-called also Repairing Units (RUs) in this study- can self-organize into a mesh structure by guaranteeing Quality of Service (QoS) over the aerial link, and connecting the maximum number of EU devices. Second, we evaluate our scheme on a realistic 3D environment with buildings, and we demonstrate the effectiveness of the aerial deployment compared to a terrestrial one, in terms of coverage and wireless link reliability. Third, we address the problem of energy lifetime, and we propose a distributed charging scheduling scheme, through which a persistent coverage of RUs can be guaranteed over the emergency scenario.

STEM-mesh: Self-organizing mobile cognitive radio network for disaster recovery operations

In this paper, we address the problem of re-establishing the network connectivity in post-disaster scenarios, where the original wireless infrastructure has been partitioned into multiple network fragments (called islands), operating on different frequencies. To this purpose, we propose the utilization of swarms of dedicated repairing units, called Stem-Nodes (SNs). SNs are provided with Cognitive Radio (CR) and self-positioning capabilities, in order to offer maximum reconfigurability in terms of mobility and wireless technologies supported. Moreover, swarms of SNs can self-organize into STEM-Mesh structure, that works as a dynamic backbone to connect heterogeneous islands using different technologies (e.g. Wi-Fi, Wi-MAX, etc). In this paper, we present three contributions pertaining to STEM-Mesh: (i) we describe a distributed motion control scheme (based on virtual springs approach) that enables SNs to self-organize into dynamic STEM-Mesh structures, (ii) we introduce a discovery scheme, through which SNs can explore the scenario in both spatial and frequency domains, and possibly connect the islands to the STEM-Mesh backbone and (iii) we validate the correctness of the proposed scheme, by verifying the optimal placements of the SNs composing the STEM-Mesh on a simplified scenario (e.g. chain topology). Finally, we evaluate through Omnet++ simulations the ability of STEM-Mesh to maximally re-establish connectivity on partitioned network scenarios.

Machine-to-Machine Communication over TV White Spaces for Smart Metering Applications

Machine-to-Machine communications is envisioned to become one of the fundamental pillars of the future Internet of Things paradigm, enabling platoons of devices to be seamlessly connected and to cooperate over smart spaces. Among the possible application scenarios, smart metering represents an already existing technology that might take benefit from the capability of autonomous configuration and setup of M2M networks. At present, smart meters communicate over the 2G/3G network, however the utilization of the cellular technology poses several problems, such as low coverage and spectrum shortage over dense areas. To overcome these issues, in this paper we investigate the application of cognitive radio principles over TV White Spaces to M2M communication for the smart metering scenario. Following the recent regulations of FCC and Ofcom, that foresees the presence of a spectrum database for TV white spaces detection, we study the trade-off between protection of licensees and energy consumption in a cluster of smart meters. We provide three novel research contributions: (i) an analytical model to estimate the lifetime of a cluster of smart meters; (ii) centralized and distributed algorithms to determine the schedule operations of Master/Slave devices foreseen by the spectrum regulations; (iii) performance evaluation of the proposed framework through extensive Omnet++ simulations.

On 3-dimensional spectrum sharing for TV white and Gray Space networks

Spectrum scarcity demands for additional bandwidth where new services can be deployed on. However, todays spectrum allocation leaves almost no bands unallocated. Thus, Cognitive Radio has been studied to bring relief to the lack of spectrum, moving towards a more efficient and dynamic spectrum access. In this domain TV White Space have been proposed as a possible solution to bring new, valuable spectrum for opportunistic services. However, their availability is quite low in highly populated areas, and thus their viability is limited. This is mainly because the availability of TV White Space is typically considered at the rooftop, through two-dimensional propagation models which do not account for possible spectrum re-utilization policies within a building, or in a small-scale area. In this paper, we show that much more communication opportunities can be found when we consider also the third-dimension, i.e. the height from the terrain, and novel per-floor allocation policies. We propose three main contributions in this paper. First, we describe an analytical model through which we derive the number of available spectrum resources for indoor secondary networks, considering PU protection policies in the same building, and in surrounding buildings. Second, we estimate the number of TV Gray Space (TVGS) over realistic scenarios in candidate cities, considering realistic street topology and buildings locations, and we show that this value can be much higher than what reported in the spectrum database. Finally, we investigate co-existence of secondary networks on TVWS, when novel per-floor spectrum sharing models are used.

STEM-NET

Spontaneous wireless networks constructed out of mobile end-user devices (e.g. smartphones or tablets) are currently receiving considerable interest as they enable a wide range of novel, highly pervasive and user-centric network services and applications. In this paper, we focus on emergency-related scenarios, and we investigate the potential of spontaneous networks for providing Internet connectivity over the emergency area through the sharing of resources owned by the end-user devices. Novel and extremely flexible network deployment strategies are required in order to cope with the user mobility, the limited communication capabilities of wireless devices, and the intrinsic dynamics of traffic loads and QoS requirements. To this purpose, we propose here a novel approach toward the deployment of spontaneous networks composed by a new generation of wireless devices - called Stem Nodes (SNs) - to emphasize their ability to cover multiple network roles (e.g. gateway, router). The self-organization of the spontaneous network is then achieved through the local reconfiguration of each SN. Two complementary research contributions are provided. First, we describe the software architecture of a SN (which can be implemented on top of existing end-user devices), and we detail how a SN can manage its role set, eventually extending it through cooperation with other SNs. Second, we propose distributed algorithms, based on swarm intelligence principles, through which each SN can autonomously select its role, and self-elect to gateway or router, so that end-to-end performance are maximized while the lifetime of the spontaneous emergency network is prolonged. The ability of the proposed algorithm to guarantee adaptive and self-organizing network behaviors is demonstrated through extensive Omnet++ simulations, and through a prototype implementation of the SN architecture on a real testbed.

Re-establishing network connectivity in post-disaster scenarios through mobile cognitive radio networks

Network interoperability and self-organization constitute important communication requirements in disaster recovery scenarios. Here, the original communication infrastructure might be partially or completely damaged, and the whole network might be partitioned into segments (called islands in the following) that might operate on different frequencies/wireless technologies. In this paper, we investigate techniques to maximally re-establish the connectivity among heterogeneous islands through the utilization of specialized repairing units called Stem Nodes (SNs). A SN combines spectrum reconfigurability (offered by the Software Defined Radio technology) with self-positioning and dynamic routing functionalities, and thus it is able to replace damaged components of the original infrastructure. Moreover, sets of SNs can self-organize into multi-hop mesh structures connecting heterogeneous islands. We study the problem of determining the optimal deployment of SNs so that the number of connected devices of the original network is maximized. Given the NP-hardness of the problem, we propose approximated solutions with reduced computational complexity. We then compare the centralized solution with a distributed algorithm (based on virtual springs approach) that enables SNs to explore the environment in both space/frequency domains, and to self-organize into virtual mesh structures. Simulation results confirm the effectiveness of the distributed algorithm to maximally re-establish the network connectivity even on large-scale scenarios.

Distributed Mobile Femto-Databases for Cognitive Access to TV White Spaces

Nowadays several mobile applications connect to the internet through 2G/3G/LTE, which are becoming more crowded. Cognitive wireless networks have been proposed as a possible solution to supply additional bandwidth, and more recently TV White Spaces (TVWS) have been investigated as one candidate. TVWS devices should contact a remote spectrum database, which will reply with the channels available to use. It is not specified how devices should contact the remote spectrum database, so in this work we focus on the usage of a cellular connection, where however the number of the queries could rapidly grow and occupy considerable bandwidth. In this paper we present the idea of Femto-Databases, i.e. devices which act as distributed mobile databases able to satisfy the spectrum requests by opportunistic devices. Extensive simulations through the Omnet++ platform show that our approach can effectively reduce the load on the cellular infrastructure, and improve the latency of the query communication to the remote spectrum database.

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.

Dynamic Adaptive Video Streaming on Heterogeneous TVWS and Wi-Fi Networks

Nowadays, people usually connect to the Internet through a multitude of different devices. Video streaming takes the lion’s share of the bandwidth, and represents the real challenge for the service providers and for the research community. At the same time, most of the connections come from indoor, where Wi-Fi already experiences congestion and coverage holes, directly translating into a poor experience for the user. A possible relief comes from the TV white space (TVWS) networks, which can enhance the communication range thanks to sub-GHz frequencies and favorable propagation characteristics, but offer slower datarates compared with other 802.11 protocols. In this paper, we show the benefits that TVWS networks can bring to the end user, and we present CABA, a connection aware balancing algorithm able to exploit multiple radio connections in the favor of a better user experience. Our experimental results indicate that the TVWS network can effectively provide a wider communication range, but a load balancing middleware between the available connections on the device must be used to achieve better performance. We conclude this paper by presenting real data coming from field trials in which we streamed an MPEG dynamic adaptive streaming over HTTP video over TVWS and Wi-Fi. Practical quantitative results on the achievable quality of experience for the end user are then reported. Our results show that balancing the load between Wi-Fi and TVWS can provide a higher playback quality (up to 15% of average quality index) in scenarios in which the Wi-Fi is received at a low strength.

Connectivity recovery in post-disaster scenarios through Cognitive Radio swarms

In the aftermath of a natural calamity, relief operations can be hindered by damages to the terrestrial infrastructures (e.g. cellular base stations) that might lead to the disruption of wireless communication services. As a result, network partitions made up of isolated End-User (EU) devices, heterogeneous in terms of wireless access technologies and transmitting frequency bands, can occur within the scenario. In this paper, we address the problem of how to deploy a temporary and dynamic wireless network in order to quickly re-establish the end-to-end connectivity among isolated devices in a post-disaster environment. To this purpose, we propose the utilization of Repairing Units (RUs), consisting of Unmanned Ground Vehicles (UGVs) equipped with multiple Cognitive Radio (CR) devices; swarms of RUs are able to self-organize into a Repairing Mesh Network (RMN) that connects the isolated EU devices. Three main contributions are provided in this paper. First, we address the theoretical problem of determining the optimal deployment of the RMN (in terms of position and channel allocation on each RU), so that the number of connected EU devices is maximized, given a constrained number of available RUs. We further divide the deployment problem into a multi-channel spatial coverage and mesh connectivity problems, and we provide an approximated (optimal) solution. Second, we propose a distributed algorithm-based on the virtual spring force model-through which the RUs are able to explore the scenario in terms of space/frequency, and to create the RMN. Third, we evaluate connectivity and adaptiveness of the distributed solution through extensive Omnet++ simulations and a small scale test-bed. Simulation results show that the distributed RMN deployment algorithm provides performance close to the approximated solution in terms of covered EU devices. Experimental results demonstrate the ability of the distributed virtual spring model to adapt to dynamic propagation conditions, in order to maximize the quality of the wireless links of the RMN.