Med en ökande tillväxt inom flygtrafikbranschen behöver de bakomliggande flygtrafikledningssystemen uppgraderas för att möta den växande komplexiteten i syfte att säkerställa en ordnad flygtrafik. Här anses det arkitekturella konceptet System Wide Information Management (SWIM) för distribuerade flygledningssystem vara lösningen för att bygga system som är lättare att underhålla och enklare kan kan samverka med varandra. År 2021 fastslog Europeiska unionen att samtliga operativa intressenter inom det aeronautiska informationsutbytet i EU skall tillhandahålla och kunna konsumera SWIM-tjänster och erbjöd då en uppsättning tjänstegränssnittsbindningar för intressenter att hävda foglighet med för att efterfölja de nya regleringarna. Bland dessa finner vi AMQP Messaging och WS Light som utiliserar AMQP respektive HTTP som meddelandeprotokoll. Tidigare forskning har visat att AMQP presterar bättre än HTTP inom de flesta områden, men denna studie undersöker om någon av de två lämpar sig bättre som meddelandeprotokoll för en europabaserad SWIM-implementation genom att analysera resultatet i en SWIM-kontext. Med hjälp av en komparativ analys och kvantitativ dataanalys jämförs de två meddelandeprotokollen i denna studie för att identifiera liknande och åtskiljande karaktärsdrag samt för att svara på om någon av de två lämpar sig bättre för ändamålet. De punkter protokollen jämförs på är struktur, overhead och effektivitet, interoperabilitet och kompabilitet, tillförlitlighet och feltolerans samt förekomster i Eurocontrols SWIM Registry. Studiens resultat visar att AMQP är den lämpligaste kandidaten av de två sett till implementationstrender och prestanda, men att det är bör göras en avvägning innan en intressent väljer vilket gränssnitt denne skall implementera. / With an increasing growth within the aviation industry, the underlying air traffic control systems needs to be upgraded to meet the growing complexity for ensuring an organized air traffic. This is where the architectural concept System Wide Information Management (SWIM) for distributed air traffic control systems is believed to be the solution for building systems that are easier to maintain and can cooperate with ease. In the year 2021, the European Union decided that all operative stakeholders within the aeronautical information exchange in EU shall provide and be able to consume SWIM services, and provided a set of service interface bindings for stakeholders to claim conformance to in order to follow the new regulations. Among these we find AMQP Messaging and WS Light that utilizes AMQP and HTTP, respectively, as messaging protocols. Previous research has shown that AMQP performs better than HTTP in most areas, but this study analyses the result in a SWIM context to see if any of the two is a more suitable messaging protocol in a Europe based SWIM implementation. Through a comparative analysis and a quantitative data analysis the two messaging protocols are compared in this study to identify similar and distinctive characteristics to answer whether one of the two is a better candidate for the purpose. The protocols are compared on their structure, overhead and efficiency, interoperability and fault tolerance, and their occurances in Eurocontrol's SWIM Registry. The result of the study shows that AMQP is the more suitable candidate of the two, in regards to trends in current implementations as well as performance metrics, but a stakeholder should make a trade-off before choosing what service interface binding to implement.

Connected aviation, the Internet of Flying Things and related emerging technologies, such as the System-Wide Information Management infrastructure of the FAA NextGen program, present numerous opportunities for the aviation sector. The ubiquity of aeronautical, flight, weather, aerodrome, and maintenance data accelerates the development of smarter software systems to cope with the ever increasing requirements of the industry sector. The increasing amount, frequency and variety of real-time data available to modern air transport and tactical systems, and their crews, creates exciting new challenges and research opportunities. We present an architectural approach toward the vision of increasingly self-separating and self-governed flight operations within the bigger picture of an evolving set of future Autonomous Flight Rules. The challenges in this field of research are manifold and include autonomic airborne trajectory optimization, data sharing, fusion and information derivation, the incorporation of and communication with rational actors—both human and machine—via a connected aviation infrastructure, to facilitate smarter decision making and support while generating economical, environmental and tactical advantages. We developed a concept and prototype implementation of our Smart Autoflight Control System. The concept and implemented system follow the design principle of an Autonomic Element, consisting of an Autonomic Manager and its Managed Element, acting within an Autonomic Context. The Managed Element concept embraces an infrastructure featuring suitable models of manageable environments, airborne agents, planners, applicable operational cost and risk policies, and connections to the System-Wide Information Management cloud as well as to relevant rational actors, such as Air Traffic Control, Command and Control, Operations or Dispatch. The Autonomic Manager concept incorporates the extraction, that is, short-term sensing, of features from operational scenarios and the categorization of these scenarios according to their level of criticality and associated flight phase. The Autonomic Manager component, furthermore, continuously tunes, that is, actuates, manageable items of its Managed Element, such as environments and planners, and triggers competitions to assess their performance under the various extracted and dynamically changing features of their Autonomic Context. The performance reputations of the tuned manageable items are collected in a knowledge base and may serve as a long-term sensor. Both the managed items of the Managed Element as well the managing items of the Autonomic Manager are extendable and may realize very different paradigms, including deterministic, non-deterministic, heuristically guided, and biologically inspired approaches. We assessed the extensibility and maintainability of our Smart Autoflight Control System infrastructure by including manageable environments and planners of the Classical Grid Search, Probabilistic Roadmaps, and Rapidly-Exploring Random Trees families into its core component. Furthermore, we evaluated the viability of a simple heuristic and a more sophisticated Sequential Model-Based Algorithm Configuration Autonomic Manager to adaptively select and tune manageable planners of the supported families based on the extracted features from very simple to highly challenging scenarios. We were able to show that a self-adaptive approach, that heuristically tunes and selects the best performing planner following a performance competition, produces suitable flight trajectories within reasonable deliberation times. Additionally, we discovered options for improving our heuristic Autonomic Manager through a series of evaluation runs of the Sequential Model-Based Algorithm Configuration Autonomic Manager. Our contributions answer how the manageable items, that is, environments and planners, of our Smart Autoflight Control System core component have to be modified in order to embed System-Wide Information Management data that feature both spatial and temporal aspects. We show how operational cost and risk policies help to assess environments differently and plan suitable flight trajectories accordingly. We identify and implement the necessary extensions and capabilities that have to be supported by manageable and managing items, respectively, to enable continuous feature extraction, adaptive tuning, performance competitions, and planner selection in dynamic flight scenarios. / Graduate