Abstract
Today’s distributed applications require steady maintenance. To tackle this problem, so-called self-adaptive systems (SAS) can be used to change the behaviour automatically to adapt to a changing environment and context. Open challenges remain when those SAS get combined with Systems of Systems (SoS). SoS can get partitioned in multiple sub-parts as a result of errors or connection faults which rises the need for a decentralized self-adaptation approach in SoS. In this doctoral paper, those open challenges are discussed and explained using a scenario of self-driving vehicles. Ideas for solving the problems are presented and the evaluation method of using the Webots simulation environment is explained. Solving the problems of self-adaptive SoS will enable robust adaptations in large-scale systems.
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This work is funded by the German Research Foundation (DFG) within the Research Training Group Role-based Software Infrastructures for continuous-context-sensitive Systems (GRK 1907).
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Matusek, D. (2020). Decentralized Self-adaptation in Large-Scaled Systems of Systems. In: Muccini, H., et al. Software Architecture. ECSA 2020. Communications in Computer and Information Science, vol 1269. Springer, Cham. https://doi.org/10.1007/978-3-030-59155-7_3
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