A multi-objective optimization approach for analysing and architecting system of systems

Sillmann, Bjorn; Glock, Thomas; Ghassemi, Raziyeh; Sax, Eric

doi:10.1109/syscon.2018.8369581

Cited by 5 publications

(7 citation statements)

References 7 publications

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“…Despite their dissemination, they have not drawn the attention of the SoS community. On the other hand, studies have focused on mathematical modeling or simulation-based methods over the last years, possibly because they can quantitatively evaluate speciic behaviors of SoS dynamic architectures with considerable accuracy and lower human resources [7,61,111]. By involving a smaller number of stakeholders if compared with scenario-based methods (which usually require a large number of stakeholders from diferent distributed organizations, mainly in the case of SoS), mathematical modeling or simulation-based methods become cheaper in terms of human resources involved, but require specialized skills for their successful application.…”

Section: Rq3: Which Is the Maturity Level Of The Methods That Evaluat...mentioning

confidence: 99%

“…The studies adopted the Tradespace Exploration (TSE) methods for analyzing the SoS architectural alternatives space. Such methods generate and analyze the space of possible architectural alternatives (i.e., a set of good architectural solutions) based on a given set of design constraints [111]. The solutions can be used as inputs of the detailed design phase, where the best architecture is possibly produced [112].…”

Section: Mathematical Modeling and Simulation-based Approachesmentioning

confidence: 99%

“…The solutions can be used as inputs of the detailed design phase, where the best architecture is possibly produced [112]. The number of alternatives for SoS architectures can be very large, mainly due to the number of constituent system variants and integration possibilities [111]. The analysis of the SoS architectural alternatives is usually an impossible human task, since it demands long time and many resources [111]; therefore, techniques that automate such analysis are relevant because they can reduce the number of alternatives to be dealt with in the next phase.…”

Section: Mathematical Modeling and Simulation-based Approachesmentioning

confidence: 99%

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Evaluation of Systems-of-Systems Software Architectures: State of the Art and Future Perspectives

et al. 2022

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The quality of large and complex Systems-of-Systems (SoS) that have emerged in critical application domains depends on the quality of their architectures, which are inherently dynamic in terms of reorganization at runtime to comply with domain needs. However, the way to model and evaluate the quality of these architectures is not clear. This article presents the state of the art regarding how SoS architectures have been evaluated. For this, we systematically examined the literature and, as a result, we discovered and summarized relevant architectural evaluation methods and associated modeling techniques and quality attributes, the maturity of these methods, as well as the benefits and costs of adopting them. We also address open issues and research opportunities and recommend that the mindset for SoS architecture evaluation must be changed to ensure the quality of SoS in critical domains.

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Section: Rq3: Which Is the Maturity Level Of The Methods That Evaluat...mentioning

confidence: 99%

Section: Mathematical Modeling and Simulation-based Approachesmentioning

confidence: 99%

Section: Mathematical Modeling and Simulation-based Approachesmentioning

confidence: 99%

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Evaluation of Systems-of-Systems Software Architectures: State of the Art and Future Perspectives

et al. 2022

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“…Lastly, another variation of an automotive software component in the form of agents is present. Here, Sillmann et al [85] provide an approach focusing on describing the electric powertrain software architecture as an agent-based system. Of course, the architectural approaches mentioned above also use the term components to describe both the system architecture and the system behaviour: AUTOSAR, FOCUS, AADL, UML, SysML, or the Palladio Component Model to mention some of them.…”

Section: Component-based Architecturementioning

confidence: 99%

Model-based resource analysis and synthesis of service-oriented automotive software architectures

2021

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Context Automotive software architectures describe distributed functionality by an interaction of software components. One drawback of today’s architectures is their strong integration into the onboard communication network based on predefined dependencies at design time. The idea is to reduce this rigid integration and technological dependencies. To this end, service-oriented architecture offers a suitable methodology since network communication is dynamically established at run-time. Aim We target to provide a methodology for analysing hardware resources and synthesising automotive service-oriented architectures based on platform-independent service models. Subsequently, we focus on transforming these models into a platform-specific architecture realisation process following AUTOSAR Adaptive. Approach For the platform-independent part, we apply the concepts of design space exploration and simulation to analyse and synthesise deployment configurations, i. e., mapping services to hardware resources at an early development stage. We refine these configurations to AUTOSAR Adaptive software architecture models representing the necessary input for a subsequent implementation process for the platform-specific part. Result We present deployment configurations that are optimal for the usage of a given set of computing resources currently under consideration for our next generation of E/E architecture. We also provide simulation results that demonstrate the ability of these configurations to meet the run time requirements. Both results helped us to decide whether a particular configuration can be implemented. As a possible software toolchain for this purpose, we finally provide a prototype. Conclusion The use of models and their analysis are proper means to get there, but the quality and speed of development must also be considered.

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“…The results of both scoring criteria were merged and all papers with an aggregated score of at least 6 were included in the literature list. Complementing this list with our previous two articles [ 19 , 20 ] and four manually added papers [ 64 , 65 , 66 , 67 ], resulted into a total of 46 papers [ 19 , 20 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 ,…”

Section: Requirements For the Enterprise Architecturementioning

confidence: 99%

A Design of the Resilient Enterprise: A Reference Architecture for Emergent Behaviors Control

Bemthuis

Iacob

Havinga

2020

Sensors

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The sooner disruptive emergent behaviors are detected, the sooner preventive measures can be taken to ensure the resilience of business processes execution. Therefore, organizations need to prepare for emergent behaviors by embedding corrective control mechanisms, which help coordinate organization-wide behavior (and goals) with the behavior of local autonomous entities. Ongoing technological advances, brought by the Industry 4.0 and cyber-physical systems of systems paradigms, can support integration within complex enterprises, such as supply chains. In this paper, we propose a reference enterprise architecture for the detection and monitoring of emergent behaviors in enterprises. We focus on addressing the need for an adequate reaction to disruptions. Based on a systematic review of the literature on the topic of current architectural designs for understanding emergent behaviors, we distill architectural requirements. Our architecture is a hybrid as it combines distributed autonomous business logic (expressed in terms of simple business rules) and some central control mechanisms. We exemplify the instantiation and use of this architecture by means of a proof-of-concept implementation, using a multimodal logistics case study. The obtained results provide a basis for achieving supply chain resilience “by design”, i.e., through the design of coordination mechanisms that are well equipped to absorb and compensate for the effects of emergent disruptive behaviors.

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A multi-objective optimization approach for analysing and architecting system of systems

Cited by 5 publications

References 7 publications

Evaluation of Systems-of-Systems Software Architectures: State of the Art and Future Perspectives

Evaluation of Systems-of-Systems Software Architectures: State of the Art and Future Perspectives

Model-based resource analysis and synthesis of service-oriented automotive software architectures

A Design of the Resilient Enterprise: A Reference Architecture for Emergent Behaviors Control

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