TY - BOOK A1 - Wätzoldt, Sebastian A1 - Giese, Holger T1 - Modeling collaborations in self-adaptive systems of systems BT - terms, characteristics, requirements, and scenarios N2 - An increasing demand on functionality and flexibility leads to an integration of beforehand isolated system solutions building a so-called System of Systems (SoS). Furthermore, the overall SoS should be adaptive to react on changing requirements and environmental conditions. Due SoS are composed of different independent systems that may join or leave the overall SoS at arbitrary point in times, the SoS structure varies during the systems lifetime and the overall SoS behavior emerges from the capabilities of the contained subsystems. In such complex system ensembles new demands of understanding the interaction among subsystems, the coupling of shared system knowledge and the influence of local adaptation strategies to the overall resulting system behavior arise. In this report, we formulate research questions with the focus of modeling interactions between system parts inside a SoS. Furthermore, we define our notion of important system types and terms by retrieving the current state of the art from literature. Having a common understanding of SoS, we discuss a set of typical SoS characteristics and derive general requirements for a collaboration modeling language. Additionally, we retrieve a broad spectrum of real scenarios and frameworks from literature and discuss how these scenarios cope with different characteristics of SoS. Finally, we discuss the state of the art for existing modeling languages that cope with collaborations for different system types such as SoS. N2 - Steigende Anforderungen zum Funktionsumfang und der Flexibilität von Systemen führt zur Integration von zuvor isolierten Systemlösungen zu sogenannten System of Systems (SoS). Weiterhin sollten solche SoS adaptive Eigenschaften aufweisen, die es ihm ermöglichen auf sich ändernde Anforderungen und Umwelteinflüsse zu reagieren. Weil SoS aus unterschiedlichen, unabhängigen Subsystemen zusammengesetzt sind, die wiederum das übergeordnete SoS zu beliebigen Zeitpunkten erweitern oder verlassen können, ist das SoS durch eine variable Systemstruktur gekennzeichnet. Weiterhin definieren sich der Funktionsumfang des SoS und dessen Potenzial aus den enthaltenen Subsystemen. Solche komplexen Systemzusammenstellungen erfordern neue Untersuchungstechniken, um die Interaktion der einzelnen Subsysteme, die Kopplung von geteilten Daten und den Einfluss von lokalen Adaptionsstrategien auf das Gesamtsystem besser verstehen zu können. In diesem Bericht formulieren wir aktuelle Forschungsfragen mit dem Fokus auf der Modellierung von Interaktionen zwischen verschiedenen Systemteilen innerhalt eines SoS. Weiterhin definieren wir wichtige Systemtypen und Begriffe aus diesem Bereich durch das Zusammentragen aktueller Literatur. Nachdem wir ein gemeinsames Verständnis über SoS geschaffen haben, leiten wir typische SoS Eigenschaften und allgemeine Anforderungen für eine Modellierungssprache für Kollaborationen ab. Zusätzlich führen wir eine Literaturstudie durch, in der wir ein breites Spektrum von realen Szenarios und existierenden Frameworks zusammentragen, an denen wir die aufgezeigten SoS Eigenschaften diskutieren. Abschließend beschreiben wir den Stand der Wissenschaft bezüglich existierender Modellierungssprachen, die sich mit Kollaborationen in verschiedenen Arten von Systemen, wie SoS, beschäftigen. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 96 KW - modeling KW - collaboration KW - system of systems KW - cyber-physical systems KW - feedback loops KW - adaptive systems KW - Modellierung KW - Kollaborationen KW - System of Systems KW - Cyber-Physical Systems KW - Feedback Loops KW - adaptive Systeme Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-73036 SN - 978-3-86956-324-4 SN - 1613-5652 SN - 2191-1665 IS - 96 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Giese, Holger Burkhard T1 - Software Engineering for Smart Cyber-Physical Systems BT - Challenges and Opportunities T2 - Proceedings of the 12th Innovations on Software Engineering Conference N2 - Currently, a transformation of our technical world into a networked technical world where besides the embedded systems with their interaction with the physical world the interconnection of these nodes in the cyber world becomes a reality can be observed. In parallel nowadays there is a strong trend to employ artificial intelligence techniques and in particular machine learning to make software behave smart. Often cyber-physical systems must be self-adaptive at the level of the individual systems to operate as elements in open, dynamic, and deviating overall structures and to adapt to open and dynamic contexts while being developed, operated, evolved, and governed independently. In this presentation, we will first discuss the envisioned future scenarios for cyber-physical systems with an emphasis on the synergies networking can offer and then characterize which challenges for the design, production, and operation of these systems result. We will then discuss to what extent our current capabilities, in particular concerning software engineering match these challenges and where substantial improvements for the software engineering are crucial. In today's software engineering for embedded systems models are used to plan systems upfront to maximize envisioned properties on the one hand and minimize cost on the other hand. When applying the same ideas to software for smart cyber-physical systems, it soon turned out that for these systems often somehow more subtle links between the involved models and the requirements, users, and environment exist. Self-adaptation and runtime models have been advocated as concepts to covers the demands that result from these subtler links. Lately, both trends have been brought together more thoroughly by the notion of self-aware computing systems. We will review the underlying causes, discuss some our work in this direction, and outline related open challenges and potential for future approaches to software engineering for smart cyber-physical systems. KW - Software Engineering KW - Cyber-Physical Systems KW - Self-aware computing systems Y1 - 2019 SN - 978-1-4503-6215-3 U6 - https://doi.org/10.1145/3299771.3301650 PB - Association for Computing Machinery CY - New York ER -