Flexible cross layer optimization for fixed and mobile broadband telecommunication networks and beyond

In der heutigen Zeit, in der das Internet im Allgemeinen und Telekommunikationsnetze im Speziellen kritische Infrastrukturen erreicht haben, entstehen hohe Anforderungen und neue Herausforderungen an den Datentransport in Hinsicht auf Effizienz und Flexibilität. Heutige Telekommunikationsnetze sind jedoch rigide und statisch konzipiert, was nur ein geringes Maß an Flexibilität und Anpassungsfähigkeit der Netze ermöglicht und darüber hinaus nur im begrenzten Maße die Wichtigkeit von Datenflüssen im wiederspiegelt. Diverse Lösungsansätze zum kompletten Neuentwurf als auch zum evolutionären Konzept des Internet wurden ausgearbeitet und spezifiziert, um diese neuartigen Anforderungen und Herausforderungen adäquat zu adressieren. Einer dieser Ansätze ist das Cross Layer Optimierungs-Paradigma, welches eine bisher nicht mögliche direkte Kommunikation zwischen verteilten Funktionalitäten unterschiedlichen Typs ermöglicht, um ein höheres Maß an Dienstgüte zu erlangen. Ein wesentlicher Indikator, welcher die Relevanz dieses Ansatzes unterstreicht, zeichnet sich durch die Programmierbarkeit von Netzwerkfunktionalitäten aus, welche sich aus der Evolution von heutigen hin zu zukünftigen Netzen erkennen lässt. Dieses Konzept wird als ein vielversprechender Lösungsansatz für Kontrollmechanismen von Diensten in zukünftigen Kernnetzwerken erachtet. Dennoch existiert zur Zeit der Entstehung dieser Doktorarbeit kein Ansatz zur Cross Layer Optimierung in Festnetz-und Mobilfunknetze, welcher der geforderten Effizienz und Flexibilität gerecht wird. Die übergeordnete Zielsetzung dieser Arbeit adressiert die Konzeptionierung, Entwicklung und Evaluierung eines Cross Layer Optimierungsansatzes für Telekommunikationsnetze. Einen wesentlichen Schwerpunkt dieser Arbeit stellt die Definition einer theoretischen Konzeptionierung und deren praktischer Realisierung eines Systems zur Cross Layer Optimierung für Telekommunikationsnetze dar. Die durch diese Doktorarbeit analysierten wissenschaftlichen Fragestellungen betreffen u.a. die Anwendbarkeit von Cross Layer Optimierungsansätzen auf Telekommunikationsnetzwerke; die Betrachtung neuartiger Anforderungen; existierende Konzepte, Ansätze und Lösungen; die Abdeckung neuer Funktionalitäten durch bereits existierende Lösungen; und letztendlich den erkennbaren Mehrwert des neu vorgeschlagenen Konzepts gegenüber den bestehenden Lösungen. Die wissenschaftlichen Beiträge dieser Doktorarbeit lassen sich grob durch vier Säulen skizzieren: Erstens werden der Stand der Wissenschaft und Technik analysiert und bewertet, Anforderungen erhoben und eine Lückenanalyse vorgenommen. Zweitens werden Herausforderungen, Möglichkeiten, Limitierungen und Konzeptionierungsaspekte eines Modells zur Cross Layer Optimierung analysiert und evaluiert. Drittens wird ein konzeptionelles Modell - Generic Adaptive Resource Control (GARC) - spezifiziert, als Prototyp realisiert und ausgiebig validiert. Viertens werden theoretische und praktische Beiträge dieser Doktorarbeit vertiefend analysiert und bewertet.As the telecommunication world moves towards a data-only network environment, signaling, voice and other data are similarly transported as Internet Protocol packets. New requirements, challenges and opportunities are bound to this transition and influence telecommunication architectures accordingly. In this time in which the Internet in general, and telecommunication networks in particular, have entered critical infrastructures and systems, it is of high importance to guarantee efficient and flexible data transport. A certain level of Quality-of-Service (QoS) for critical services is crucial even during overload situations in the access and core network, as these two are the bottlenecks in the network. However, the current telecommunication architecture is rigid and static, which offers very limited flexibility and adaptability. Several concepts on clean slate as well as evolutionary approaches have been proposed and defined in order to cope with these new challenges and requirements. One of these approaches is the Cross Layer Optimization paradigm. This concept omits the strict separation and isolation of the Application-, Control- and Network-Layers as it enables interaction and fosters Cross Layer Optimization among them. One indicator underlying this trend is the programmability of network functions, which emerges clearly during the telecommunication network evolution towards the Future Internet. The concept is regarded as one solution for service control in future mobile core networks. However, no standardized approach for Cross Layer signaling nor optimizations in between the individual layers have been standardized at the time this thesis was written. The main objective of this thesis is the design, implementation and evaluation of a Cross Layer Optimization concept on telecommunication networks. A major emphasis is given to the definition of a theoretical model and its practical realization through the implementation of a Cross Layer network resource optimization system for telecommunication systems. The key questions answered through this thesis are: in which way can the Cross Layer Optimization paradigm be applied on telecommunication networks; which new requirements arise; which of the required functionalities cannot be covered through existing solutions, what other conceptual approaches already exist and finally whether such a new concept is viable. The work presented in this thesis and its contributions can be summarized in four parts: First, a review of related work, a requirement analysis and a gap analysis were performed. Second, challenges, limitations, opportunities and design aspects for specifying an optimization model between application and network layer were formulated. Third, a conceptual model - Generic Adaptive Resource Control (GARC) - was specified and its prototypical implementation was realized. Fourth, the theoretical and practical thesis contributions was validated and evaluated

Strategies for Combatting the Climate Crisis: Policy, Organizing, and Community Resilience

This portfolio synthesizes work I have done throughout graduate school through research and experience. I have had the opportunity to focus the majority of my work on the climate crisis and be involved in work to address this wicked problem. Though detrimental impacts are already being felt, the IPCC reports that humans can still prevent the worst effects of climate change. This is a problem that needs to be addressed on a variety of fronts. My portfolio discusses combating climate change at a federal, state, and community level. It highlights different strategies that will need to be utilized, including policy change, community organizing, and resilience.https://scholarworks.umt.edu/grad_portfolios/1332/thumbnail.jp

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas