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The concept of programmable networks is radically changing the way communication infrastructures are designed, integrated, and operated. Currently, the topic is spearheaded by concepts such as software-defined networking, forwarding and control element separation, and network function virtualization. Notably, software-defined networking has attracted significant attention in telecommunication and data centers and thus already in some production-grade networks.
Despite the prevalence of software-defined networking in these domains, industrial networks are yet to see its benefits to encourage adoption. However, the misconceptions around the concept itself, the role of virtualization, and algorithms pose a significant obstacle.
Furthermore, the desire to accommodate new services in the automation industry results in a pattern of constantly increasing complexity of industrial networks, which is compounded by the requirement to provide stringent deterministic service guarantees considering characteristically different applications and thus posing a significant challenge for management, configuration, and maintenance as existing solutions are architecturally inflexible.
Therefore, the first contribution of this thesis addresses the misconceptions around software-defined networking by providing a comparative analysis of programmable network concepts, detailing where software-defined networks compare with other concepts and how its principles can be leveraged to evolve industrial networks.
Armed with the fundamental principles of programmable networks, the second contribution identifies virtualization technologies and proposes novel algorithms to provide varied quality of service guarantees on converged time-sensitive Ethernet networks using software-defined networking concepts.
Finally, a performance analysis of a software-defined hybrid deployment solution for control and management of time-sensitive Ethernet networks that integrates proposed novel algorithms is presented as an industrial use-case that enables industrial operators to harness the full potential of time-sensitive networks.
Die vorliegende Arbeit untersucht auf Basis einer umfassenden weltweiten empirischen Befragung die Arbeitsweise und das Entscheidungsverhalten von Private Equity Professionals in der Transaktionspraxis. Ausgehend von einer empirischen Beurteilung von Due Diligence mit Hinblick auf die Notwendigkeit ihrer Durchführung im Kontext von Informations- und Prognoseproblem zeigt die Untersuchung auf, wie sich die quantitative Arbeit in der Private Equity Praxis ausgestaltet und ordnet diese in ihrem Zusammenspiel mit weichen Faktoren und Expertenwissen bzw. persönlicher Erfahrung ein. Zuletzt wird auf Basis der verfügbaren Daten eine Brücke zwischen Einsatz & Rolle quantitativer Methoden und weicher Faktoren bei der Investitionsentscheidung und der Performance von Private Equity Gesellschaften geschlagen.
Die Arbeit gliedert sich in folgende sechs Hauptabschnitte:
- Einleitung
- Aktuelle Forschung zu Private Equity und Motivation der Arbeit
- Private Equity – eine Einführung
- Grundlegende Informationsprobleme und Unsicherheiten bei einem Unternehmenskauf: Informationsasymmetrien und Prognoseproblem
- Empirische Untersuchung: Due Diligence im Private Equity – Einsatz und Rolle quantitativer Methoden bei Private Equity Transaktionen
- Schlussbemerkung und Ausblick