@misc{BrandGiese2019,
  author    = {Brand, Thomas and Giese, Holger Burkhard},
  title     = {Towards Generic Adaptive Monitoring},
  series = {2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)},
  journal   = {2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-1-5386-5172-8},
  issn      = {1949-3673},
  doi       = {10.1109/SASO.2018.00027},
  pages     = {156 -- 161},
  year      = {2019},
  abstract  = {Monitoring is a key prerequisite for self-adaptive software and many other forms of operating software. Monitoring relevant lower level phenomena like the occurrences of exceptions and diagnosis data requires to carefully examine which detailed information is really necessary and feasible to monitor. Adaptive monitoring permits observing a greater variety of details with less overhead, if most of the time the MAPE-K loop can operate using only a small subset of all those details. However, engineering such an adaptive monitoring is a major engineering effort on its own that further complicates the development of self-adaptive software. The proposed approach overcomes the outlined problems by providing generic adaptive monitoring via runtime models. It reduces the effort to introduce and apply adaptive monitoring by avoiding additional development effort for controlling the monitoring adaptation. Although the generic approach is independent from the monitoring purpose, it still allows for substantial savings regarding the monitoring resource consumption as demonstrated by an example.},
  language  = {en}
}
@misc{BrandGiese2019,
  author    = {Brand, Thomas and Giese, Holger},
  title     = {Generic adaptive monitoring based on executed architecture runtime model queries and events},
  series = {IEEE Xplore},
  journal   = {IEEE Xplore},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-1-7281-2731-6},
  issn      = {1949-3673},
  doi       = {10.1109/SASO.2019.00012},
  pages     = {17 -- 22},
  year      = {2019},
  abstract  = {Monitoring is a key functionality for automated decision making as it is performed by self-adaptive systems, too. Effective monitoring provides the relevant information on time. This can be achieved with exhaustive monitoring causing a high overhead consumption of economical and ecological resources. In contrast, our generic adaptive monitoring approach supports effectiveness with increased efficiency. Also, it adapts to changes regarding the information demand and the monitored system without additional configuration and software implementation effort. The approach observes the executions of runtime model queries and processes change events to determine the currently required monitoring configuration. In this paper we explicate different possibilities to use the approach and evaluate their characteristics regarding the phenomenon detection time and the monitoring effort. Our approach allows balancing between those two characteristics. This makes it an interesting option for the monitoring function of self-adaptive systems because for them usually very short-lived phenomena are not relevant.},
  language  = {en}
}