Abstract
This chapter defines three reference scenarios to which other chapters may refer for the purpose of motivating and illustrating architectures, techniques, and methods consistently throughout the book. The reference scenarios cover a broad set of characteristics and issues that one may encounter in self-aware systems and represent a range of domains and a variety of scales and levels of complexity. The first scenario focuses on an adaptive sorting algorithm and exemplifies how a self-aware system may adapt to changes in the data on which it operates, the environment in which it executes, or the requirements or performance criteria to which it manages itself. The second focuses on self-aware multiagent applications running in a data center environment, allowing issues of collective behavior in cooperative and competitive self-aware systems to come to the fore. The third focuses on a cyber-physical system. It allows us to explore many of the same issues of system-level self-awareness that appear in the second scenario, but in a different context and at a potentially even larger (potentially planetary) scale, when there is no one clear global objective.
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Acknowledgements
This work was partially supported by the Swedish Research Council (VR) for the projects “Cloud Control” and “Power and temperature control for large-scale computing infrastructures,” and through the LCCC Linnaeus and ELLIIT Excellence Centers.
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Kephart, J.O. et al. (2017). Reference Scenarios for Self-aware Computing. In: Kounev, S., Kephart, J., Milenkoski, A., Zhu, X. (eds) Self-Aware Computing Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-47474-8_4
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