51 research outputs found

    Advanced SDN-Based QoS and Security Solutions for Heterogeneous Networks

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    This thesis tries to study how SDN can be employed in order to support Quality of Service and how the support of this functionality is fundamental for today networks. Considering, not only the present networks, but also the next generation ones, the importance of the SDN paradigm become manifest as the use of satellite networks, which can be useful considering their broadcasting capabilities. For these reasons, this research focuses its attention on satellite - terrestrial networks and in particular on the use of SDN inside this environment. An important fact to be taken into account is that the growing of the information technologies has pave the way for new possible threats. This research study tries to cover also this problem considering how SDN can be employed for the detection of past and future malware inside networks

    Five Facets of 6G: Research Challenges and Opportunities

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    Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components

    Cyber Security

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    This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

    Cartography

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    The terrestrial space is the place of interaction of natural and social systems. The cartography is an essential tool to understand the complexity of these systems, their interaction and evolution. This brings the cartography to an important place in the modern world. The book presents several contributions at different areas and activities showing the importance of the cartography to the perception and organization of the territory. Learning with the past or understanding the present the use of cartography is presented as a way of looking to almost all themes of the knowledge

    Remote Sensing

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    This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

    Optical Wireless Data Center Networks

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    Bandwidth and computation-intensive Big Data applications in disciplines like social media, bio- and nano-informatics, Internet-of-Things (IoT), and real-time analytics, are pushing existing access and core (backbone) networks as well as Data Center Networks (DCNs) to their limits. Next generation DCNs must support continuously increasing network traffic while satisfying minimum performance requirements of latency, reliability, flexibility and scalability. Therefore, a larger number of cables (i.e., copper-cables and fiber optics) may be required in conventional wired DCNs. In addition to limiting the possible topologies, large number of cables may result into design and development problems related to wire ducting and maintenance, heat dissipation, and power consumption. To address the cabling complexity in wired DCNs, we propose OWCells, a class of optical wireless cellular data center network architectures in which fixed line of sight (LOS) optical wireless communication (OWC) links are used to connect the racks arranged in regular polygonal topologies. We present the OWCell DCN architecture, develop its theoretical underpinnings, and investigate routing protocols and OWC transceiver design. To realize a fully wireless DCN, servers in racks must also be connected using OWC links. There is, however, a difficulty of connecting multiple adjacent network components, such as servers in a rack, using point-to-point LOS links. To overcome this problem, we propose and validate the feasibility of an FSO-Bus to connect multiple adjacent network components using NLOS point-to-point OWC links. Finally, to complete the design of the OWC transceiver, we develop a new class of strictly and rearrangeably non-blocking multicast optical switches in which multicast is performed efficiently at the physical optical (lower) layer rather than upper layers (e.g., application layer). Advisors: Jitender S. Deogun and Dennis R. Alexande

    Variational methods and its applications to computer vision

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    Many computer vision applications such as image segmentation can be formulated in a ''variational'' way as energy minimization problems. Unfortunately, the computational task of minimizing these energies is usually difficult as it generally involves non convex functions in a space with thousands of dimensions and often the associated combinatorial problems are NP-hard to solve. Furthermore, they are ill-posed inverse problems and therefore are extremely sensitive to perturbations (e.g. noise). For this reason in order to compute a physically reliable approximation from given noisy data, it is necessary to incorporate into the mathematical model appropriate regularizations that require complex computations. The main aim of this work is to describe variational segmentation methods that are particularly effective for curvilinear structures. Due to their complex geometry, classical regularization techniques cannot be adopted because they lead to the loss of most of low contrasted details. In contrast, the proposed method not only better preserves curvilinear structures, but also reconnects some parts that may have been disconnected by noise. Moreover, it can be easily extensible to graphs and successfully applied to different types of data such as medical imagery (i.e. vessels, hearth coronaries etc), material samples (i.e. concrete) and satellite signals (i.e. streets, rivers etc.). In particular, we will show results and performances about an implementation targeting new generation of High Performance Computing (HPC) architectures where different types of coprocessors cooperate. The involved dataset consists of approximately 200 images of cracks, captured in three different tunnels by a robotic machine designed for the European ROBO-SPECT project.Open Acces

    Fault-tolerant satellite computing with modern semiconductors

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    Miniaturized satellites enable a variety space missions which were in the past infeasible, impractical or uneconomical with traditionally-designed heavier spacecraft. Especially CubeSats can be launched and manufactured rapidly at low cost from commercial components, even in academic environments. However, due to their low reliability and brief lifetime, they are usually not considered suitable for life- and safety-critical services, complex multi-phased solar-system-exploration missions, and missions with a longer duration. Commercial electronics are key to satellite miniaturization, but also responsible for their low reliability: Until 2019, there existed no reliable or fault-tolerant computer architectures suitable for very small satellites. To overcome this deficit, a novel on-board-computer architecture is described in this thesis.Robustness is assured without resorting to radiation hardening, but through software measures implemented within a robust-by-design multiprocessor-system-on-chip. This fault-tolerant architecture is component-wise simple and can dynamically adapt to changing performance requirements throughout a mission. It can support graceful aging by exploiting FPGA-reconfiguration and mixed-criticality.  Experimentally, we achieve 1.94W power consumption at 300Mhz with a Xilinx Kintex Ultrascale+ proof-of-concept, which is well within the powerbudget range of current 2U CubeSats. To our knowledge, this is the first COTS-based, reproducible on-board-computer architecture that can offer strong fault coverage even for small CubeSats.European Space AgencyComputer Systems, Imagery and Medi
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