Towards a Rigorous Modeling Formalism for Systems of Systems

Gezgin, Tayfun; Etzien, Christoph; Henkler, Stefan; Rettberg, Achim

doi:10.1109/isorcw.2012.42

Cited by 29 publications

(27 citation statements)

References 18 publications

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“…In [7], the authors propose a formalism for relating basics SoS concepts by means of a UML class diagram. They identify as basic concepts SystemType, System-OfSystems, Goal, Role, Service, Requirement, Port, Requirement and Port.…”

Section: Adls In Sos Architectural Frameworkmentioning

confidence: 99%

AMADEOS Framework and Supporting Tools

Babu

Iacob

Lollini

et al. 2016

Cyber-Physical Systems of Systems

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Section: Adls In Sos Architectural Frameworkmentioning

confidence: 99%

AMADEOS Framework and Supporting Tools

Babu

Iacob

Lollini

et al. 2016

Cyber-Physical Systems of Systems

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“…First, because a SoS consists of several interconnected and diverse system types ranging from small embedded systems over cyber-physical systems to software intensive systems, it inherits such system characteristics as adaptiveness, collaborativity and flexibility. Second, a SoS is able to combine single capabilities by system interaction to offer new services or functionalities that cannot be realized by a single system alone [39,81,130,140]. Third, the complexity of the overall SoS raises challenges in describing, analyzing and understanding the emerged system behavior.…”

Section: Research Challenges and Goalsmentioning

confidence: 99%

“…There, unreliable sensor networks, mobile devices and different software systems must be spontaneously interconnected and coordinated to handle the catastrophic situation appropriately. On the other hand, the inherent distributed nature of SoS, the complexity of contained systems as well as their interaction raises challenges for the development, understanding and execution of such systems [58,81,111,127].…”

Section: Introductionmentioning

confidence: 99%

“…Due to the causal connection, all changes in the runtime model will affect the running system itself, which allows an adaptive control of the software system on a much higher level of abstraction directly working with the corresponding runtime models [32,38]. Furthermore, because adaptive SoS are complex and inherent distributed [81,130] new challenges concerning the knowledge management arise. For example, if systems inside the adaptive SoS interact with each other to reach common goals, they must communicate with each other or share information for coordination purposes to agree on a common knowledge base for further task processing.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the modeling language must have a clear semantic for the runtime models itself, its access by the adaptation logic as well as between different systems inside the SoS. Even worse, an adaptive SoS is inherent distributed with emergent behavior [39,81,130,140]. Therefore, contained systems must collaborate with each other to reach SoS goals by simultaneously optimize their own behavior according to local goals.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Collaborations in Adaptive Systems of Systems

Wätzoldt

Giese

2015

Proceedings of the 2015 European Conference on Software Architecture Workshops

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Recently, due to an increasing demand on functionality and flexibility, beforehand isolated systems have become interconnected to gain powerful adaptive System of Systems (SoS) solutions with an overall robust, flexible and emergent behavior. The adaptive SoS comprises a variety of different system types ranging from small embedded to adaptive cyber-physical systems. On the one hand, each system is independent, follows a local strategy and optimizes its behavior to reach its goals. On the other hand, systems must cooperate with each other to enrich the overall functionality to jointly perform on the SoS level reaching global goals, which cannot be satisfied by one system alone. Due to difficulties of local and global behavior optimizations conflicts may arise between systems that have to be solved by the adaptive SoS.This thesis proposes a modeling language that facilitates the description of an adaptive SoS by considering the adaptation capabilities in form of feedback loops as first class entities. Moreover, this thesis adopts the Models@runtime approach to integrate the available knowledge in the systems as runtime models into the modeled adaptation logic. Furthermore, the modeling language focuses on the description of system interactions within the adaptive SoS to reason about individual system functionality and how it emerges via collaborations to an overall joint SoS behavior. Therefore, the modeling language approach enables the specification of local adaptive system behavior, the integration of knowledge in form of runtime models and the joint interactions via collaboration to place the available adaptive behavior in an overall layered, adaptive SoS architecture.Beside the modeling language, this thesis proposes analysis rules to investigate the modeled adaptive SoS, which enables the detection of architectural patterns as well as design flaws and pinpoints to possible system threats. Moreover, a simulation framework is presented, which allows the direct execution of the modeled SoS architecture. Therefore, the analysis rules and the simulation framework can be used to verify the interplay between systems as well as the modeled adaptation effects within the SoS. This thesis realizes the proposed concepts of the modeling language by mapping them to a state of the art standard from the automotive domain and thus, showing their applicability to actual systems. Finally, the modeling language approach is evaluated by remodeling up to date research scenarios from different domains, which demonstrates that the modeling language concepts are powerful enough to cope with a broad range of existing research problems.-I - Zusammenfassung

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