342 research outputs found

    Evolutionary Games on Weighted and Spatial Networks

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    Spectrum Sensing and Multiple Access Schemes for Cognitive Radio Networks

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    Increasing demands on the radio spectrum have driven wireless engineers to rethink approaches by which devices should access this natural, and arguably scarce, re- source. Cognitive Radio (CR) has arisen as a new wireless communication paradigm aimed at solving the spectrum underutilization problem. In this thesis, we explore a novel variety of techniques aimed at spectrum sensing which serves as a fundamental mechanism to find unused portions of the electromagnetic spectrum. We present several spectrum sensing methods based on multiple antennas and evaluate their receiving operating characteristics. We study a cyclostationary feature detection technique by means of multiple cyclic frequencies. We make use of a spec- trum sensing method called sequential analysis that allows us to significantly decrease the time needed for detecting the presence of a licensed user. We extend this scheme allowing each CR user to perform the sequential analysis algorithm and send their local decision to a fusion centre. This enables for an average faster and more accurate detection. We present an original technique for accounting for spatial and temporal cor- relation influence in spectrum sensing. This reflects on the impact of the scattering environment on detection methods using multiple antennas. The approach is based on the scattering geometry and resulting correlation properties of the received signal at each CR device. Finally, the problem of spectrum sharing for CR networks is addressed in or- der to take advantage of the detected unused frequency bands. We proposed a new multiple access scheme based on the Game Theory. We examine the scenario where a random number of CR users (considered as players) compete to access the radio spec- trum. We calculate the optimal probability of transmission which maximizes the CR throughput along with the minimum harm caused to the licensed users’ performance

    Proceedings of the NASA Conference on Space Telerobotics, volume 1

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    The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty

    5G network slicing for rural connectivity: multi-tenancy in wireless networks

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    As the need for wireless broadband continues to grow around the world, there is an increasing focus to minimise the existing digital divide and ensuring that everyone receives high-quality internet services, especially the inhabitants of rural areas. As a result, different technological solutions are being studied and trialled for improving rural connectivity, such as 5G with dynamic spectrum access. One of the architectures of 5G is network slicing, which supports network virtualisation and consists of independent logical networks, called slices, on the 5G network. Network slicing supports the multi-tenancy of different operators on the same physical network, and this feature is known as neutral host networks (NHN). It allows multiple operators to co-exist on the same physical network but on different virtual networks to serve end users. Generally, the 5G NHN deployment is handled by an infrastructure provider (InP), who could be a mobile network operator (MNO), an Internet service provider, a third-party operator, etc. At the same time, potential tenants would lease slices from the InP. The NHN strategy would help reduce resource duplication and increase the utilisation of existing resources. The existing research into NHN for small cells, in-building connectivity solutions, and other deployment scenarios help to understand the technological and business requirements. End-to-end sharing across operators to provide services to their end users is another innovative application of 5G NHN that has been tested for dense areas. Meanwhile, the feasibility and policy impact of NHN is not studied extensively for the rural scenario. The research in this thesis examines the use of NHN in macro- and small-cell networks for 5G communication systems to minimise the digital divide, with a special focus on rural areas. The study also presents and analyses the 5G multi-tenancy system design for the rural wireless scenario, focusing mainly on exploring suitable business cases through network economics, techno-economic study, and game theory analysis. The results obtained from the study, such as cost analysis, business models, sensitivity analysis, and pricing strategies, help in formulating the policy on infrastructure sharing to improve rural connectivity. The contributions of the thesis are useful for stakeholders and policymakers to assess the suitability of the rural 5G NHN by exploring state-of-the-art technologies, techno-economic analysis, sensitivity analysis, newer business models, investment assessment, cost allocation, and risk sharing. Initially, the research gap is highlighted through the extensive literature review and stakeholders’ views on rural connectivity collected from discussions with them. First, the in-depth discussion on the network economics of the rural 5G NHN includes the study of potential future scenarios, value network configurations, spectrum access strategy models, and business models. Secondly, the techno-economic analysis studies the key performance indicators (KPI), cost analysis, return on investment, net present value, and sensitivity analysis, with the application for the rural parts of the UK and India. Finally, the game theory framework includes the study of strategic interaction among the two key stakeholders, InP and the MNO, using models such as investment games and pricing strategies during multi-tenancy. The research concludes by presenting the contribution towards the knowledge and future work.As the need for wireless broadband continues to grow around the world, there is an increasing focus to minimise the existing digital divide and ensuring that everyone receives high-quality internet services, especially the inhabitants of rural areas. As a result, different technological solutions are being studied and trialled for improving rural connectivity, such as 5G with dynamic spectrum access. One of the architectures of 5G is network slicing, which supports network virtualisation and consists of independent logical networks, called slices, on the 5G network. Network slicing supports the multi-tenancy of different operators on the same physical network, and this feature is known as neutral host networks (NHN). It allows multiple operators to co-exist on the same physical network but on different virtual networks to serve end users. Generally, the 5G NHN deployment is handled by an infrastructure provider (InP), who could be a mobile network operator (MNO), an Internet service provider, a third-party operator, etc. At the same time, potential tenants would lease slices from the InP. The NHN strategy would help reduce resource duplication and increase the utilisation of existing resources. The existing research into NHN for small cells, in-building connectivity solutions, and other deployment scenarios help to understand the technological and business requirements. End-to-end sharing across operators to provide services to their end users is another innovative application of 5G NHN that has been tested for dense areas. Meanwhile, the feasibility and policy impact of NHN is not studied extensively for the rural scenario. The research in this thesis examines the use of NHN in macro- and small-cell networks for 5G communication systems to minimise the digital divide, with a special focus on rural areas. The study also presents and analyses the 5G multi-tenancy system design for the rural wireless scenario, focusing mainly on exploring suitable business cases through network economics, techno-economic study, and game theory analysis. The results obtained from the study, such as cost analysis, business models, sensitivity analysis, and pricing strategies, help in formulating the policy on infrastructure sharing to improve rural connectivity. The contributions of the thesis are useful for stakeholders and policymakers to assess the suitability of the rural 5G NHN by exploring state-of-the-art technologies, techno-economic analysis, sensitivity analysis, newer business models, investment assessment, cost allocation, and risk sharing. Initially, the research gap is highlighted through the extensive literature review and stakeholders’ views on rural connectivity collected from discussions with them. First, the in-depth discussion on the network economics of the rural 5G NHN includes the study of potential future scenarios, value network configurations, spectrum access strategy models, and business models. Secondly, the techno-economic analysis studies the key performance indicators (KPI), cost analysis, return on investment, net present value, and sensitivity analysis, with the application for the rural parts of the UK and India. Finally, the game theory framework includes the study of strategic interaction among the two key stakeholders, InP and the MNO, using models such as investment games and pricing strategies during multi-tenancy. The research concludes by presenting the contribution towards the knowledge and future work

    Interactive Machine Learning for User-Innovation Toolkits – An Action Design Research approach

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    Machine learning offers great potential to developers and end users in the creative industries. However, to better support creative software developers' needs and empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. This thesis asks the following research questions: How can we apply a user-centred approach to the design of developer tools for rapid prototyping with Interactive Machine Learning? In what ways can we design better developer tools to accelerate and broaden innovation with machine learning? This thesis presents a three-year longitudinal action research study that I undertook within a multi-institutional consortium leading the EU H2020 -funded Innovation Action RAPID-MIX. The scope of the research presented here was the application of a user-centred approach to the design and evaluation of developer tools for rapid prototyping and product development with machine learning. This thesis presents my work in collaboration with other members of RAPID-MIX, including design and deployment of a user-centred methodology for the project, interventions for gathering requirements with RAPID-MIX consortium stakeholders and end users, and prototyping, development and evaluation of a software development toolkit for interactive machine learning. This thesis contributes with new understanding about the consequences and implications of a user-centred approach to the design and evaluation of developer tools for rapid prototyping of interactive machine learning systems. This includes 1) new understanding about the goals, needs, expectations, and challenges facing creative machine-learning non-expert developers and 2) an evaluation of the usability and design trade-offs of a toolkit for rapid prototyping with interactive machine learning. This thesis also contributes with 3) a methods framework of User-Centred Design Actions for harmonising User-Centred Design with Action Research and supporting the collaboration between action researchers and practitioners working in rapid innovation actions, and 4) recommendations for applying Action Research and User-Centred Design in similar contexts and scale

    Using MapReduce Streaming for Distributed Life Simulation on the Cloud

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    Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

    From Digital Twins to Digital Selves and Beyond

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    This open access book aims at deepening the understanding of the relation between cyber-physical systems (CPSs) as socio-technical systems and their digital representations with intertwined artificial intelligence (AI). The authors describe why it is crucial for digital selves to be able to develop emotional behavior and why a humanity-inspired AI is necessary so that humans and humanoids can coexist. The introductory chapter describes major milestones in computer science which form the basis for the implementation of digital twins and digital selves. The subsequent Part I then lays the foundation to develop a socio-technical understanding of the nature of digital twins as representations and trans-human development objects. Following the conceptual understanding of digital twins and how they could be engineered according to cognitive and organizational structures, Part II forms the groundwork for understanding social behavior and its modeling. It discusses various perception-based socio-emotional approaches before sketching behavior-relevant models and their simulation capabilities. In particular, it is shown how emotions can substantially influence the collective behavior of artificial actors. Part III eventually presents a symbiosis showing under which preconditions digital selves might construct and produce digital twins as integrated design elements in trans-human ecosystems. The chapters in this part are dedicated to opportunities and modes of co-creating reflective socio-trans-human systems based on digital twin models, exploring mutual control and continuous development. The final epilog is congenitally speculative in its nature by presenting thoughts on future developments of artificial life in computational substrates. The book is written for researchers and professionals in areas like cyber-physical systems, robotics, social simulation or systems engineering, interested to take a speculative look into the future of digital twins and autonomous agents. It also touches upon philosophical aspects of digital twins, digital selves and humanoids
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