1,721,016 research outputs found
Fast Multiattribute Network Selection Technique for Vertical Handover in Heterogeneous Emergency Communication Systems
No full textThe telecommunication infrastructure in emergency scenarios is necessarily composed of heterogeneous radio/mobile portions. Mobile Nodes (MNs) equipped with multiple network interfaces can assure continuous communications when different Radio Access Networks (RANs) that employ different Radio Access Technologies (RATs) are available. In this context, the paper proposes the definition of a Decision Maker (DM), within the protocol stack of the MN, in charge of performing network selections and handover decisions. The DM has been designed to optimize one or more performance metrics and it is based on Multiattribute Decision Making (MADM) methods. Among several MADM techniques considered, taken from the literature, the work is then focused on the TOPSIS approach, which allows introducing some improvements aimed at reducing the computational burden needed to select the RAT to be employed. The enhanced method is called Dynamic-TOPSIS (D-TOPSIS). Finally, the numerical results, obtained through a large simulative campaign and aimed at comparing the performance and the running time of the D-TOPSIS, the TOPSIS, and the algorithms found in the literature, are reported and discussed
QoS Optimisation of eMBB Services in Converged 5G-Satellite Networks
No full textThe integration of satellite communications into 5G ecosystem is pivotal to boost enhanced mobile broadband (eMBB) services in highly dynamic scenarios and in areas not optimally supported by terrestrial infrastructures. Given the heterogeneity of the networks involved, network slicing is key networking paradigm to ensure different grades of quality of service (QoS) based on the users' and verticals' requirements. In this light, this paper proposes an optimisation framework able to exploit the available resources allocated to the defined network slices so as to meet the diverse QoS/QoE requirements exposed by the network actors. Resource allocation schemes built upon neural network algorithms are validated through extensive simulation campaigns that have shown the superiority of the proposed concepts with respect to other solution candidates available from the literature
State of the art and innovative communications and networking solutions for a reliable and efficient interplanetary internet
No full textIn the last few years deep space exploration missions are undergoing a significant transformation as are the expectations of their scientific investigators and the public who participate in these experiences. National Aeronautics and Space Administration (NASA) and European Space Agency (ESA), recently, decided pursuing a mission to study Jupiter and its moons, and another to visit the largest moons of Saturn. Those missions need new communication and networking infrastructures able to support space exploration, to connect scientists and their instruments, and also to involve the public via common web interfaces. A possible solution is represented by the so called InterPlaNetary (IPN) Internet that introduces new challenges in the field of deep space communications.
In that framework, the paper proposes a description of the challenging scenario, surveys its technical problems and envisages possible advanced communications and networking solutions starting from the analysis of a specific IPN architecture. In more detail, we study the network performance changes due to the nodes’ movements from the communications and the networking viewpoint. It represents the main contribution of the paper and opens the doors to future advanced solutions suited to be employed in the IPN Internet
Performance Analysis of VCA-based Target Detection System for Maritime Surveillance
No full textIn the latest years great importance and research efforts have been put into safety and security aspects concerning the vehicular framework. In this connection, maritime surveillance is playing an important role, since situation awareness proves fundamental to ensure safety conditions at sea. In this work, we propose a novel maritime surveillance system based on Video Content Analysis, where vessel detection is performed automatically by a remote Machine Learning based target identification algorithm. As performance study, we carry out experimental tests analyzing the impact of packet loss, compression rate and transport protocol type on ship-to-ground communication over a satellite link, and their joint effects on video quality, transmission time and vessel detection accuracy
On the Localization of Wireless Targets: A Drone Surveillance Perspective
No full textRemotely piloted vehicles have become more and more popular in recent years due to their increased availability on the market. In general, drones can represent a threat for public safety due to their potential misuse. This motivation gives rise to the need of devising specific methods and techniques to monitor sensitive areas, in order to deploy effective drone surveillance systems. These systems are designed to detect nearby undesired targets, and to neutralize impending threats. One of the main tasks involved in this scenarios is target localization, which can be performed with different approaches. In particular, in this article we carry out a study on the main literature works related to the framework of wireless target localization based on RF and WiFi techniques, providing a thorough analysis on the perspective of their deployment in drone surveillance applications
Innovative Flying Strategy based on Drone Energy Profile: an Application for Traffic Monitoring
No full textUnmanned aerial vehicles (UAVs) are increasingly utilized in smart cities to perform traffic monitoring tasks such as multiple object detection and tracking. The task's criticality is dependent on the drones' dynamic altitude, movable camera, and various viewing angles. These challenges are addressed once the UAVs' collected data is received. However, parameters affecting drone data collecting flight operations must also be explored, including drone actual flight time, data collection time, and energy consumption profile. The drone flight time would depend upon the battery capacity and energy consumption profile, which comprises drone movement, data collection, and communication energies. Besides, data collection energy consumption is subjected to video quality, frame rates, and data compression. The installed battery in UAVs is of limited capacity and determining actual flight time, data collection time, and energy consumption profile based on the factors mentioned above is critical. This paper develops and examines a drone energy consumption profile and proposes a drone flight strategy in a surveillance scenario to correctly estimate the drone's actual flight time, data collection time, and the distance the drone could travel from its original location. The results of this analysis are presented as a test case for flying a drone to collect the traffic monitoring data
Social Drone Sharing to Increase UAV Patrolling Autonomy in Pre- and Post-Emergency Scenarios
No full textMultirotor drones are becoming increasingly popular in a number of application fields, with a unique appeal to the scientific community and the general public. Applications include security, monitoring and surveillance, environmental mapping, and emergency scenario management: in all these areas, two of the main issues to address are the availability of appropriate software architectures to coordinate teams of drones and solutions to cope with the short-term battery life. This article proposes the novel concepts of Social Drone Sharing (SDS) and Social Charging Station (SCS), which provide the basis to address these problems. Specifically, the article focuses on teams of drones in pre- and post-event monitoring and assessment. Using multirotor drones in these situations can be difficult due to the limited flight autonomy when multiple targets need to be inspected. The idea behind the SDS concept is that citizens can volunteer to recharge a drone or replace its batteries if it lands on their property. The computation of paths to inspect multiple targets will then take into account the availability of SCSs to find solutions compatible with the required inspection and flight times. The main contribution of this article is the development of a cloud-based software architecture for SDS mission management, which includes a multi-drone path-optimization algorithm taking the SDS and SCS concepts into account. Experiments in simulation and a lab environment are discussed, paving the path to a larger trial in a real scenario
Towards IoT-based ehealth services: A smart prototype system for home rehabilitation
No full textIn the latest years we have been witnessing an evolution of the technological framework thanks to the Internet of Things paradigm, which is enabling innovative smart services for many different applications. The healthcare system is among the main scenarios that are benefiting from this new trend, thus giving rise to the concept of eHealth. In this framework we propose SmartPANTS, an IoT-based wireless system specifically designed for the rehabilitation of lower limbs. Our system is conceived as a prototype of a medical platform to be employed during the physical therapy for patients recovering from a brain stroke condition. SmartPANTS includes a signal processing and machine learning algorithm able to automatically recognize the type of exercise the patient is performing, and to provide real-time feedback on the execution. Moreover, experimental tests show that our platform is able to estimate the execution time of the different exercises, providing values very close to real ones. Performance results show that the SmartPANTS system is able to correctly identify the type of exercise currently being performed with an accuracy of about 99%
Outdoor Places of Interest Recognition Using WiFi Fingerprints
No full textThe growing interest in concepts such as smart cities and smart mobility is giving more and more importance to place of interest (POI) information, which proves to be crucial in providing efficient and tailored location-based services (LBSs). Though plenty of solutions exist for recognizing indoor places, the literature lacks of approaches aimed at recognizing big outdoor places without the GPS employment. Even if GPS-based solutions assure great accuracy, they have a strong request in terms of energy necessary to achieve such result. As a consequence, if LBSs are thought on the move (e.g., mobile devices such as smartphones are used) energy consumption is a key constraint. This paper proposes a POI recognition algorithm called enhanced location recognition algorithm for automatic check-in applications (E-LRACI). It is an evolution of LRACI (Location Recognition Algorithm for automatic Check-In applications, originally reported in [I. Bisio, F. Lavagetto, M. Marchese, and A. Sciarrone, ''GPS/HPS-andwifi fingerprint-based location recognition for check-in applications over smartphones in cloud-based LBSS,'' IEEE Transactions on Multimedia, vol. 15, no. 4, pp. 858-869, Jun. 2013]) which aims at recognizing big outdoor places by only exploiting radio beacons emitted by WiFi access points. In terms of contributions, this paper first, proposes a novel fingerprint algorithm; second, solves the problem of big outdoor POI recognition without using GPS by leveraging the concept of spot; and third, compares the results obtained by E-LRACI and other reference works both in terms of recognition accuracy and computational complexity. The obtained numerical results, carried out on real data (acquired with Android-based smartphones), prove that E-LRACI provides the best results since it is able to guarantee the highest accuracy (95% versus, at most, 89%) at a lowest computational complexity with respect to the existing POI recognition algorithms
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