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CoalaViz: Supporting Traceability of Adaptation Decisions in Pervasive Communication Systems

Martin Pfannemüller; Markus Weckesser; Roland Kluge; Janick Edinger; Manisha Luthra; Robin Klose; Christian Becker; Andy Schürr
In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE International Conference on Pervasive Computing and Communications (PerCom-2019), 22nd International Conference on Pervasive Computing and Communications, Pages 590-595, IEEE, 3/2019.


Today's pervasive communication systems are highly configurable to adapt themselves dynamically to continuously changing contexts of the system such as varying workloads and user preferences. For a particular context, usually numerous valid system configurations exist, and each configuration may perform differently in terms of nonfunctional properties like energy consumption or task throughput. For tackling these challenges, in previous work, we introduced Coala, a model-based adaptation approach to derive optimal system configurations considering multiple performance goals. In this paper, we present CoalaViz, a novel tool for visualizing the self-adaptive behavior of pervasive communication systems. With CoalaViz, we provide a tool for making adaptation decisions in self-adaptive pervasive communication systems traceable while being applicable for a wide range of use cases. CoalaViz (i) visualizes the system performance over time, (ii) visualizes the system state as context feature model and graph-based network view, (iii) allows the user to change priorities of performance goals interactively, and (iv) provides a modular, extensible design. We demonstrate the applicability of CoalaViz using three pervasive system use cases.