Monitoring for control in role-oriented self-adaptive systems

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Abstract

Self-adaptive Systems (SASs) are one way to address the ever-growing complexity of software systems by allowing the system to react on changes in its operating environment. In today's systems, self-adaptation is typically realized with a control loop, for which the MAPE-K feedback loop is a prominent example. Research uses the notion of patterns to describe the distribution and decentralization of individual control loop components or control loops and their underlying managed subsystems. While there are some well-accepted standards about which components a managed sub-system has to implement so that it can interact with the control loop, research still lacks best practices for communication within and across control loops. This paper aims to identify several research challenges that exist currently in this domain. Furthermore, ideas on upcoming research to create distributed SASs that rely on roles, benchmarking and inter- and intra-loop communication for control loops will be presented. Furthermore, ongoing work on a self-adaptive distributed benchmarking application will be discussed. Finally, an evaluation strategy will be presented to provide evidence for viable results to the community.

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APA

Shmelkin, I. (2020). Monitoring for control in role-oriented self-adaptive systems. In Proceedings - 2020 IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2020 (pp. 115–119). Association for Computing Machinery, Inc. https://doi.org/10.1145/3387939.3391598

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