SeSaMe: Towards a Semantic Self Adaptive Middleware for Smart Spaces

Baresi, Luciano; Guinea, Sam; Shahzada, Adnan

doi:10.1007/978-3-642-45343-4_1

Cited by 14 publications

(21 citation statements)

References 22 publications

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“…For instance, DEECo [14], SeSaMe [15] and ASPECS [16], [17], form interactions and collaborations between different entities of a system through ensembles, groups and holarchies, respectively. DEECo is an ensemble-based component system where an ensemble represents dynamic binding of a set of components and thus determines their composition and interaction.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Exchange of Distributed Partial Models@run.time for Highly Dynamic Systems

Götz

Gerostathopoulos

Křikava

et al. 2015

2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

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Abstract-Future software systems will be highly dynamic. We are already experiencing, for example, a world where CyberPhysical Systems (CPSs) play a more and more crucial role. CPSs integrate computational, physical, and networking elements; they comprise a number of subsystems, or entities, that are connected and work together. The open and highly distributed nature of the resulting system gives rise to unanticipated runtime management issues such as the organization of subsystems and resource optimization.In this paper, we focus on the problem of knowledge sharing among cooperating entities of a highly distributed and selfadaptive CPS. Specifically, the research question we address is how to minimize the knowledge that needs to be shared among the entities of a CPS. If all entities share all their knowledge with each other, the performance, energy and memory consumption as well as privacy are unnecessarily negatively impacted. To reduce the amount of knowledge to share between CPS entities, we envision a role-based adaptive knowledge exchange technique working on partial runtime models, i.e., models reflecting only part of the state of the CPS. Our approach supports two adaptation dimensions: the runtime type of knowledge and conditions over the knowledge. We illustrate the feasibility of our technique by discussing its realization based on two state-of-the-art approaches.

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Section: Related Workmentioning

confidence: 99%

Adaptive Exchange of Distributed Partial Models@run.time for Highly Dynamic Systems

Götz

Gerostathopoulos

Křikava

et al. 2015

2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

Self Cite

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“…For example, Baresi et al [25] propose the SeSaMe middleware that consists of a component and management layer. The middleware facilitates the modeling of collaboration aspects, but focuses on the definition of black box components instead of feedback loops.…”

Section: State Of the Artmentioning

confidence: 99%

“…Therefore, the software module template class in the Deurema metamodel inherits from the behavior model class as shown in Figure 5. 25. Similar to black box activities, a software module template is defined by an optional domain trigger and a corresponding action that points to the implementation of the domain functionality.…”

Section: Software Module Templatementioning

confidence: 99%

“…25. They follow the Deurema naming scheme and thus, are labeled with their name and the stereotype «SoftwareModuleTemplate».…”

Section: Concrete Syntaxmentioning

confidence: 99%

“…Finally, a very interesting approach from the domain of smart spaces called SeSaMe [25] introduces an adaptive middleware infrastructure. The advantage of this approach is that existing components, as massively available in smart spaces in form of sensors or devices, can connect to the middleware to exchange data or interact with each other.…”

Section: Framework With Special Focusmentioning

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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