94 research outputs found

    The American Multi-modal Energy System: Model Development with Structural and Behavioral Analysis using Hetero-functional Graph Theory

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    In the 21st century, infrastructure is playing an ever greater role in our daily lives. Presidential Policy Directive 21 emphasizes that infrastructure is critical to public confidence, the nation\u27s safety, and its well-being. With global climate change demanding a host of changes across at least four critical energy infrastructures: the electric grid, the natural gas system, the oil system, and the coal system, it is imperative to study models of these infrastructures to guide future policies and infrastructure developments. Traditionally these energy systems have been studied independently, usually in their own fields of study. Therefore, infrastructure datasets often lack the structural and dynamic elements to describe the interdependencies with other infrastructures. This thesis refers to the integration of the aforementioned energy infrastructures into a singular system-of-systems within the context of the United States of America as the American Multi-modal Energy System (AMES). This work develops an open-source structural and behavioral model of the AMES using Hetero-functional Graph Theory (HFGT), a data-driven approach, and model-based systems engineering practices in the following steps. First, the HFGT toolbox code is made available on GitHub and advanced to produce HFGs of systems on the scale of the AMES using the languages Python and Julia. Second, the analytical insights that HFGs can provide relative to formal graphs are investigated through structural analysis of the American Electric Power System which demonstrates how HFGs are better equipped to describe changes in system behavior. Third, a reference architecture of the AMES is developed, providing a standardized foundation to develop future models of the AMES. Fourth, the AMES reference architecture is instantiated into a structural model from which structural properties are investigated. Finally, a physically informed Weighted Least Squares Error Hetero-functional Graph State Estimation analysis of the AMES\u27 socio-economic behavior is implemented to investigate the behavior of the AMES with asset level granularity. These steps provide a reproducible and reusable structural and behavioral model of the AMES for guiding future policies and infrastructural developments to critical energy infrastructures

    Technologies and Applications for Big Data Value

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    This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

    Becoming a Platform in Europe

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    Emerging out of the collaborative work conducted within the Working Group “Mechanisms to activate and support the collaborative economy” of the COST Action “From Sharing to Caring: Examining Socio-Technical Aspects of the Collaborative Economy”, the book questions the varied set of organizational forms collected under the label of “collaborative” or “sharing” economy —ranging from grassroots peer-to-peer solidarity initiatives to corporate owned platforms— from the perspective of what is known as the European social values: respect for human dignity and human rights (including those of minorities), freedom, democracy, equality, and the rule of law. Therefore, the edited collection focuses on the governance of such economic activities, and how they organize labour, cooperation and social life. From individual motivations to participating, to platform use by local groups, until platform design in its political as well as technological dimensions, the book provides a comparative overview and critical discussion on the processes, narratives and organizational models at play in the collaborative economy. On such a basis, the volume offers tools, suggestions and visions for the future that may inform the designing of policies, technologies, and business models in Europe

    A distributed middleware for IT/OT convergence in modern industrial environments

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    The modern industrial environment is populated by a myriad of intelligent devices that collaborate for the accomplishment of the numerous business processes in place at the production sites. The close collaboration between humans and work machines poses new interesting challenges that industry must overcome in order to implement the new digital policies demanded by the industrial transition. The Industry 5.0 movement is a companion revolution of the previous Industry 4.0, and it relies on three characteristics that any industrial sector should have and pursue: human centrality, resilience, and sustainability. The application of the fifth industrial revolution cannot be completed without moving from the implementation of Industry 4.0-enabled platforms. The common feature found in the development of this kind of platform is the need to integrate the Information and Operational layers. Our thesis work focuses on the implementation of a platform addressing all the digitization features foreseen by the fourth industrial revolution, making the IT/OT convergence inside production plants an improvement and not a risk. Furthermore, we added modular features to our platform enabling the Industry 5.0 vision. We favored the human centrality using the mobile crowdsensing techniques and the reliability and sustainability using pluggable cloud computing services, combined with data coming from the crowd support. We achieved important and encouraging results in all the domains in which we conducted our experiments. Our IT/OT convergence-enabled platform exhibits the right performance needed to satisfy the strict requirements of production sites. The multi-layer capability of the framework enables the exploitation of data not strictly coming from work machines, allowing a more strict interaction between the company, its employees, and customers

    1982 June, Memphis State University bulletin

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    Vol. 71, No. 1 of the Memphis State University bulletin containing the undergraduate catalog for 1982-83, 1982 June.https://digitalcommons.memphis.edu/speccoll-ua-pub-bulletins/1155/thumbnail.jp

    Conceptual model for capability planning in a military context – A systems thinking approach

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    During recent decades, planning defense systems have evolved into capability-based planning (CBP) processes. This paper seeks to answer two questions: firstly, how to express a complex, real-world capability requirement; and secondly, how to assess if a system with interacting elements fulfills this requirement. We propose that both a capability need and the solution fulfilling it are expressed with a consistent set of models in a traceable manner. The models integrate current capability models, specific to planning level and capability viewpoint, with systems thinking approach. Our conceptual model defines the defense system in its environment, our data model defines and organizes the CBP terms, and our class diagram defines the CBP planning elements. We illustrate the approach by giving an example of capability parametrization and compare it both with the DODAF capability view and with the generic CBP process. Our data model describes how capabilities are degraded in action and extends the approach toward capability dynamics. The quantitative capability definition aims to support efforts to solve for real world interacting subsystems that combined implement the required capability.publishedVersionPeer reviewe

    Migrants and Refugees in Europe

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    EPDF and EPUB available Open Access under CC-BY-NC-ND licence. This book explores the labour market integration of migrants, refugees and asylum seekers across seven European countries: the Czech Republic, Denmark, Finland, Greece, Italy, Switzerland and the UK. Using empirical data from the Horizon2020 SIRIUS Project, it investigates how legal, political, social and personal circumstances combine to determine the work trajectory for migrants who choose Europe as their home

    NFV orchestration in edge and fog scenarios

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    Mención Internacional en el título de doctorLas infraestructuras de red actuales soportan una variedad diversa de servicios como video bajo demanda, video conferencias, redes sociales, sistemas de educación, o servicios de almacenamiento de fotografías. Gran parte de la población mundial ha comenzado a utilizar estos servicios, y los utilizan diariamente. Proveedores de Cloud y operadores de infraestructuras de red albergan el tráfico de red generado por estos servicios, y sus tareas de gestión no solo implican realizar el enrutamiento del tráfico, sino también el procesado del tráfico de servicios de red. Tradicionalmente, el procesado del tráfico ha sido realizado mediante aplicaciones/ programas desplegados en servidores que estaban dedicados en exclusiva a tareas concretas como la inspección de paquetes. Sin embargo, en los últimos anos los servicios de red se han virtualizado y esto ha dado lugar al paradigma de virtualización de funciones de red (Network Function Virtualization (NFV) siguiendo las siglas en ingles), en el que las funciones de red de un servicio se ejecutan en contenedores o máquinas virtuales desacopladas de la infraestructura hardware. Como resultado, el procesado de tráfico se ha ido haciendo más flexible gracias al laxo acople del software y hardware, y a la posibilidad de compartir funciones de red típicas, como firewalls, entre los distintos servicios de red. NFV facilita la automatización de operaciones de red, ya que tareas como el escalado, o la migración son típicamente llevadas a cabo mediante un conjunto de comandos previamente definidos por la tecnología de virtualización pertinente, bien mediante contenedores o máquinas virtuales. De todos modos, sigue siendo necesario decidir el en rutamiento y procesado del tráfico de cada servicio de red. En otras palabras, que servidores tienen que encargarse del procesado del tráfico, y que enlaces de la red tienen que utilizarse para que las peticiones de los usuarios lleguen a los servidores finales, es decir, el conocido como embedding problem. Bajo el paraguas del paradigma NFV, a este problema se le conoce en inglés como Virtual Network Embedding (VNE), y esta tesis utiliza el termino “NFV orchestration algorithm” para referirse a los algoritmos que resuelven este problema. El problema del VNE es NP-hard, lo cual significa que que es imposible encontrar una solución optima en un tiempo polinómico, independientemente del tamaño de la red. Como consecuencia, la comunidad investigadora y de telecomunicaciones utilizan heurísticos que encuentran soluciones de manera más rápida que productos para la resolución de problemas de optimización. Tradicionalmente, los “NFV orchestration algorithms” han intentado minimizar los costes de despliegue derivados de las soluciones asociadas. Por ejemplo, estos algoritmos intentan no consumir el ancho de banda de la red, y usar rutas cortas para no utilizar tantos recursos. Además, una tendencia reciente ha llevado a la comunidad investigadora a utilizar algoritmos que minimizan el consumo energético de los servicios desplegados, bien mediante la elección de dispositivos con un consumo energético más eficiente, o mediante el apagado de dispositivos de red en desuso. Típicamente, las restricciones de los problemas de VNE se han resumido en un conjunto de restricciones asociadas al uso de recursos y consumo energético, y las soluciones se diferenciaban por la función objetivo utilizada. Pero eso era antes de la 5a generación de redes móviles (5G) se considerase en el problema de VNE. Con la aparición del 5G, nuevos servicios de red y casos de uso entraron en escena. Los estándares hablaban de comunicaciones ultra rápidas y fiables (Ultra-Reliable and Low Latency Communications (URLLC) usando las siglas en inglés) con latencias por debajo de unos pocos milisegundos y fiabilidades del 99.999%, una banda ancha mejorada (enhanced Mobile Broadband (eMBB) usando las siglas en inglés) con notorios incrementos en el flujo de datos, e incluso la consideración de comunicaciones masivas entre maquinas (Massive Machine-Type Communications (mMTC) usando las siglas en inglés) entre dispositivos IoT. Es más, paradigmas como edge y fog computing se incorporaron a la tecnología 5G, e introducían la idea de tener dispositivos de computo más cercanos al usuario final. Como resultado, el problema del VNE tenía que incorporar los nuevos requisitos como restricciones a tener en cuenta, y toda solución debía satisfacer bajas latencias, alta fiabilidad, y mayores tasas de transmisión. Esta tesis estudia el problema des VNE, y propone algunos heurísticos que lidian con las restricciones asociadas a servicios 5G en escenarios edge y fog, es decir, las soluciones propuestas se encargan de asignar funciones virtuales de red a servidores, y deciden el enrutamiento del trafico en las infraestructuras 5G con dispositivos edge y fog. Para evaluar el rendimiento de las soluciones propuestas, esta tesis estudia en primer lugar la generación de grafos que representan redes 5G. Los mecanismos propuestos para la generación de grafos sirven para representar distintos escenarios 5G. En particular, escenarios de federación en los que varios dominios comparten recursos entre ellos. Los grafos generados también representan servidores en el edge, así como dispositivos fog con una batería limitada. Además, estos grafos tienen en cuenta los requisitos de estándares, y la demanda que se espera en las redes 5G. La generación de grafos propuesta sirve para representar escenarios federación en los que varios dominios comparten recursos entre ellos, y redes 5G con servidores edge, así como dispositivos fog estáticos o móviles con una batería limitada. Los grafos generados para infraestructuras 5G tienen en cuenta los requisitos de estándares, y la demanda de red que se espera en las redes 5G. Además, los grafos son diferentes en función de la densidad de población, y el área de estudio, es decir, si es una zona industrial, una autopista, o una zona urbana. Tras detallar la generación de grafos que representan redes 5G, esta tesis propone algoritmos de orquestación NFV para resolver con el problema del VNE. Primero, se centra en escenarios federados en los que los servicios de red se tienen que asignar no solo a la infraestructura de un dominio, sino a los recursos compartidos en la federación de dominios. Dos problemas diferentes han sido estudiados, uno es el problema del VNE propiamente dicho sobre una infraestructura federada, y el otro es la delegación de servicios de red. Es decir, si un servicio de red se debe desplegar localmente en un dominio, o en los recursos compartidos por la federación de dominios; a sabiendas de que el último caso supone el pago de cuotas por parte del dominio local a cambio del despliegue del servicio de red. En segundo lugar, esta tesis propone OKpi, un algoritmo de orquestación NFV para conseguir la calidad de servicio de las distintas slices de las redes 5G. Conceptualmente, el slicing consiste en partir la red de modo que cada servicio de red sea tratado de modo diferente dependiendo del trozo al que pertenezca. Por ejemplo, una slice de eHealth reservara los recursos de red necesarios para conseguir bajas latencias en servicios como operaciones quirúrgicas realizadas de manera remota. Cada trozo (slice) está destinado a unos servicios específicos con unos requisitos muy concretos, como alta fiabilidad, restricciones de localización, o latencias de un milisegundo. OKpi es un algoritmo de orquestación NFV que consigue satisfacer los requisitos de servicios de red en los distintos trozos, o slices de la red. Tras presentar OKpi, la tesis resuelve el problema del VNE en redes 5G con dispositivos fog estáticos y móviles. El algoritmo de orquestación NFV presentado tiene en cuenta las limitaciones de recursos de computo de los dispositivos fog, además de los problemas de falta de cobertura derivados de la movilidad de los dispositivos. Para concluir, esta tesis estudia el escalado de servicios vehiculares Vehicle-to-Network (V2N), que requieren de bajas latencias para servicios como la prevención de choques, avisos de posibles riesgos, y conducción remota. Para estos servicios, los atascos y congestiones en la carretera pueden causar el incumplimiento de los requisitos de latencia. Por tanto, es necesario anticiparse a esas circunstancias usando técnicas de series temporales que permiten saber el tráfico inminente en los siguientes minutos u horas, para así poder escalar el servicio V2N adecuadamente.Current network infrastructures handle a diverse range of network services such as video on demand services, video-conferences, social networks, educational systems, or photo storage services. These services have been embraced by a significant amount of the world population, and are used on a daily basis. Cloud providers and Network operators’ infrastructures accommodate the traffic rates that the aforementioned services generate, and their management tasks do not only involve the traffic steering, but also the processing of the network services’ traffic. Traditionally, the traffic processing has been assessed via applications/programs deployed on servers that were exclusively dedicated to a specific task as packet inspection. However, in recent years network services have stated to be virtualized and this has led to the Network Function Virtualization (Network Function Virtualization (NFV)) paradigm, in which the network functions of a service run on containers or virtual machines that are decoupled from the hardware infrastructure. As a result, the traffic processing has become more flexible because of the loose coupling between software and hardware, and the possibility of sharing common network functions, as firewalls, across multiple network services. NFV eases the automation of network operations, since scaling and migrations tasks are typically performed by a set of commands predefined by the virtualization technology, either containers or virtual machines. However, it is still necessary to decide the traffic steering and processing of every network service. In other words, which servers will hold the traffic processing, and which are the network links to be traversed so the users’ requests reach the final servers, i.e., the network embedding problem. Under the umbrella of NFV, this problem is known as Virtual Network Embedding (VNE), and this thesis refers as “NFV orchestration algorithms” to those algorithms solving such a problem. The VNE problem is a NP-hard, meaning that it is impossible to find optimal solutions in polynomial time, no matter the network size. As a consequence, the research and telecommunications community rely on heuristics that find solutions quicker than a commodity optimization solver. Traditionally, NFV orchestration algorithms have tried to minimize the deployment costs derived from their solutions. For example, they try to not exhaust the network bandwidth, and use short paths to use less network resources. Additionally, a recent tendency led the research community towards algorithms that minimize the energy consumption of the deployed services, either by selecting more energy efficient devices or by turning off those network devices that remained unused. VNE problem constraints were typically summarized in a set of resources/energy constraints, and the solutions differed on which objectives functions were aimed for. But that was before 5th generation of mobile networks (5G) were considered in the VNE problem. With the appearance of 5G, new network services and use cases started to emerge. The standards talked about Ultra Reliable Low Latency Communication (Ultra-Reliable and Low Latency Communications (URLLC)) with latencies below few milliseconds and 99.999% reliability, an enhanced mobile broadband (enhanced Mobile Broadband (eMBB)) with significant data rate increases, and even the consideration of massive machine-type communications (Massive Machine-Type Communications (mMTC)) among Internet of Things (IoT) devices. Moreover, paradigms such as edge and fog computing blended with the 5G technology to introduce the idea of having computing devices closer to the end users. As a result, the VNE problem had to incorporate the new requirements as constraints to be taken into account, and every solution should either satisfy low latencies, high reliability, or larger data rates. This thesis studies the VNE problem, and proposes some heuristics tackling the constraints related to 5G services in Edge and fog scenarios, that is, the proposed solutions assess the assignment of Virtual Network Functions to resources, and the traffic steering across 5G infrastructures that have Edge and Fog devices. To evaluate the performance of the proposed solutions, the thesis studies first the generation of graphs that represent 5G networks. The proposed mechanisms to generate graphs serve to represent diverse 5G scenarios. In particular federation scenarios in which several domains share resources among themselves. The generated graphs also represent edge servers, so as fog devices with limited battery capacity. Additionally, these graphs take into account the standard requirements, and the expected demand for 5G networks. Moreover, the graphs differ depending on the density of population, and the area of study, i.e., whether it is an industrial area, a highway, or an urban area. After detailing the generation of graphs representing the 5G networks, this thesis proposes several NFV orchestration algorithms to tackle the VNE problem. First, it focuses on federation scenarios in which network services should be assigned not only to a single domain infrastructure, but also to the shared resources of the federation of domains. Two different problems are studied, one being the VNE itself over a federated infrastructure, and the other the delegation of network services. That is, whether a network service should be deployed in a local domain, or in the pool of resources of the federation domain; knowing that the latter charges the local domain for hosting the network service. Second, the thesis proposes OKpi, a NFV orchestration algorithm to meet 5G network slices quality of service. Conceptually, network slicing consists in splitting the network so network services are treated differently based on the slice they belong to. For example, an eHealth network slice will allocate the network resources necessary to meet low latencies for network services such as remote surgery. Each network slice is devoted to specific services with very concrete requirements, as high reliability, location constraints, or 1ms latencies. OKpi is a NFV orchestration algorithm that meets the network service requirements among different slices. It is based on a multi-constrained shortest path heuristic, and its solutions satisfy latency, reliability, and location constraints. After presenting OKpi, the thesis tackles the VNE problem in 5G networks with static/moving fog devices. The presented NFV orchestration algorithm takes into account the limited computing resources of fog devices, as well as the out-of-coverage problems derived from the devices’ mobility. To conclude, this thesis studies the scaling of Vehicle-to-Network (V2N) services, which require low latencies for network services as collision avoidance, hazard warning, and remote driving. For these services, the presence of traffic jams, or high vehicular traffic congestion lead to the violation of latency requirements. Hence, it is necessary to anticipate to such circumstances by using time-series techniques that allow to derive the incoming vehicular traffic flow in the next minutes or hours, so as to scale the V2N service accordingly.The 5G Exchange (5GEx) project (2015-2018) was an EU-funded project (H2020-ICT-2014-2 grant agreement 671636). The 5G-TRANSFORMER project (2017-2019) is an EU-funded project (H2020-ICT-2016-2 grant agreement 761536). The 5G-CORAL project (2017-2019) is an EU-Taiwan project (H2020-ICT-2016-2 grant agreement 761586).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Ioannis Stavrakakis.- Secretario: Pablo Serrano Yáñez-Mingot.- Vocal: Paul Horatiu Patra

    Next Generation Supply Chains:A Roadmap for Research and Innovation

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    This open access book explores supply chains strategies to help companies face challenges such as societal emergency, digitalization, climate changes and scarcity of resources. The book identifies industrial scenarios for the next decade based on the analysis of trends at social, economic, environmental technological and political level, and examines how they may impact on supply chain processes and how to design next generation supply chains to answer these challenges. By mapping enabling technologies for supply chain innovation, the book proposes a roadmap for the full implementation of the supply chain strategies based on the integration of production and logistics processes. Case studies from process industry, discrete manufacturing, distribution and logistics, as well as ICT providers are provided, and policy recommendations are put forward to support companies in this transformative process

    Semantic querying and search in distributed ontologies

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    We have observed in recent years a continuous growth in the quantity of RDF data accessible on the web. This evolution is primarily based on increasing data on the web by different sectors such as governments, life science researchers, or academic institutes. RDF data creation is mainly developed by replacing existing data resources with RDF, changing relational databases into RDF. These RDF data are usually called qualified linked data URIs and endpoints of SPARQL. Continuous development that we are experiencing in SPARQL endpoints requires accessing sets of distributed RDF data repositories is getting popularity. This research has offered an extensive analysis of accessing RDF data across distributed ontologies. The existing approaches lack a broad mix of RDF indexing and retrieving of distributed RDF data in one package. In addition, the efficiency of the current methods is not so dynamic and mainly depend on manual fixed strategies for accessing RDF data from a distributed environment. The literature review has acknowledged the need for a robust, reliable, dynamic, and comprehensive accessing mechanism for distributed RDF data using RDF indexing. This thesis presents the conceptual framework that demonstrates the SPARQL query execution process, which accesses the data within distributed RDF sets across a stored index. This thesis introduces the semantic algebra involved in the conversion of traditional SPARQL query language into different phases. The proposed framework elaborates the concepts included in selecting, projection, joins, specialisation and generalisation operators. These operators are usually in assistance during the process of processing and converting a SPARQL query. This thesis introduces the algorithms behind the proposed conceptual framework, which covert the main SPARQL query into sub-queries, sending each subquery to the required distributed repository to fetch the data and merging the sub queries results. 4 This research demonstrates the testing of the proposed framework using the unit and functional testing strategies. The author developed and utilised the Museum ontology to test and evaluate the developed system. It demonstrates all how the complete developed and processed system works. Different tests have been performed in this thesis, like the algebraic operator's test (e.g., select, join, outer join, generalisation, and specialisation operators test) and test the proposed algorithm. After comprehensive testing, it shows that all developed system units worked as expected, and no errors found during the testing of all phases of the tested framework. Finally, the thesis presents implemented framework's performance and accuracy by comparing it to other similar systems. Evaluation of the implemented system demonstrated that the proposed framework could handle distributed SPARQL queries very effectively. The author selected FedX, ANAPSID and ADERIS existing frameworks to compare with developed system and described the results in a graphical format to illustrate the performance and accuracy of all systems
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