A Taxonomical Framework for Autonomic Computing Within Cyber-Physical Systems of Systems.
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| Title: | A Taxonomical Framework for Autonomic Computing Within Cyber-Physical Systems of Systems. |
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| Authors: | Berezovskyi, Andrii1 (AUTHOR) andriib@kth.se, Mokrushin, Leonid2 (AUTHOR), Asplund, Fredrik1 (AUTHOR), El-khoury, Jad1 (AUTHOR), Inam, Rafia1,2 (AUTHOR), Fersman, Elena2 (AUTHOR) |
| Source: | Journal of Integrated Design & Process Science. Nov2023, Vol. 27 Issue 3/4, p235-247. 13p. |
| Subjects: | Autonomic computing, Cyber physical systems, Automation software, Taxonomy, System of systems, Decentralized control systems |
| Abstract: | An increase in size and complexity prompts research of autonomous control of connected cyber-physical systems (CPS) at the level of intents (high-level goals). Domain-specific solutions such as intent-based networking, and the next generation of supervisory control and data acquisition and manufacturing execution systems, were influenced by the concept of autonomic computing and Monitor-Analyze-Plan-Execute loops over shared knowledge to introduce such control. However, there is a dearth of knowledge concerning the architectural attributes required to enable autonomic computing at a domain-independent level. CPSs are also often contributed by multiple stakeholders, thereby forming systems of systems in which architectures are by necessity federated. Herein, we apply a systematic approach to develop a taxonomy of such attributes, considering the federated nature of architectures, the need to accommodate heterogeneity and the legacy systems commonly encountered in practice. The proposed taxonomy covers nine key dimensions present within different domains of autonomic computing: knowledge representation, learning, distribution, reactivity, environment observability, information acquisition automation, information analysis automation, decision selection automation, and action implementation automation. The utility of the taxonomy is further demonstrated through an application to architectures across domains and scales. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | An increase in size and complexity prompts research of autonomous control of connected cyber-physical systems (CPS) at the level of intents (high-level goals). Domain-specific solutions such as intent-based networking, and the next generation of supervisory control and data acquisition and manufacturing execution systems, were influenced by the concept of autonomic computing and Monitor-Analyze-Plan-Execute loops over shared knowledge to introduce such control. However, there is a dearth of knowledge concerning the architectural attributes required to enable autonomic computing at a domain-independent level. CPSs are also often contributed by multiple stakeholders, thereby forming systems of systems in which architectures are by necessity federated. Herein, we apply a systematic approach to develop a taxonomy of such attributes, considering the federated nature of architectures, the need to accommodate heterogeneity and the legacy systems commonly encountered in practice. The proposed taxonomy covers nine key dimensions present within different domains of autonomic computing: knowledge representation, learning, distribution, reactivity, environment observability, information acquisition automation, information analysis automation, decision selection automation, and action implementation automation. The utility of the taxonomy is further demonstrated through an application to architectures across domains and scales. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10920617 |
| DOI: | 10.1177/10920617241295880 |
