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HAFLoop: An architecture for supporting highly adaptive feedback loops in self-adaptive systems

Author
Zavala, E.; Franch, X.; Marco, J.; Berger, C.
Type of activity
Journal article
Journal
Future generation computer systems
Date of publication
2020-04
Volume
105
First page
607
Last page
630
DOI
10.1016/j.future.2019.12.026
Project funding
Generation and Evolution of Smart APIs
Repository
http://hdl.handle.net/2117/177445 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0167739X19318448 Open in new window
Abstract
Most of the current self-adaptive systems (SASs) rely on static feedback loops such as the IBM’s MAPE-K loop for managing their adaptation process. Static loops do not allow SASs to react to runtime events such as changing adaptation requirements or MAPE-K elements’ faults. In order to address this issue, some solutions have emerged for manually or automatically perform changes on SASs’ feedback loops. However, from the software engineering perspective, most of the proposals cannot be reus...
Citation
Zavala, E. [et al.]. HAFLoop: An architecture for supporting highly adaptive feedback loops in self-adaptive systems. "Future generation computer systems", Abril 2020, vol. 105, p. 607-630.
Keywords
Adaptive feedback loop, Adaptive monitoring, IoT system, Self-adaptive system, Self-improvement, Smart vehicle
Group of research
GESSI - Group of Software and Service Engineering
inSSIDE - integrated Software, Service, Information and Data Engineering

Participants