TY - GEN
T1 - Toward Run-time Coordination of Reconfiguration Requests in Cloud Computing Systems
AU - Farhat, Salman
AU - Bliudze, Simon
AU - Duchien, Laurence
AU - Kouchnarenko, Olga
N1 - Publisher Copyright:
© 2023, IFIP International Federation for Information Processing.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Cloud applications and cyber-physical systems are becoming increasingly complex, requiring frequent reconfiguration to adapt to changing needs and requirements. Existing approaches compute new valid configurations either at design time, at runtime, or both. However, these approaches can lead to significant computational or validation overheads for each reconfiguration step. We propose a component-based approach that avoids computational and validation overheads using a representation of the set of valid configurations as a variability model. More precisely, our approach leverages feature models to automatically generate, in a component-based formalism called JavaBIP, run-time variability models that respect the feature model constraints. Produced run-time variability models enable control over application reconfiguration by executing reconfiguration requests in such a manner as to ensure the (partial) validity of all reachable configurations. We evaluate our approach on a simple web application deployed on the Heroku cloud platform. Experimental results show that the overheads induced by generated run-time models on systems involving up to 300 features are negligible, demonstrating the practical interest of our approach.
AB - Cloud applications and cyber-physical systems are becoming increasingly complex, requiring frequent reconfiguration to adapt to changing needs and requirements. Existing approaches compute new valid configurations either at design time, at runtime, or both. However, these approaches can lead to significant computational or validation overheads for each reconfiguration step. We propose a component-based approach that avoids computational and validation overheads using a representation of the set of valid configurations as a variability model. More precisely, our approach leverages feature models to automatically generate, in a component-based formalism called JavaBIP, run-time variability models that respect the feature model constraints. Produced run-time variability models enable control over application reconfiguration by executing reconfiguration requests in such a manner as to ensure the (partial) validity of all reachable configurations. We evaluate our approach on a simple web application deployed on the Heroku cloud platform. Experimental results show that the overheads induced by generated run-time models on systems involving up to 300 features are negligible, demonstrating the practical interest of our approach.
KW - Concurrent Component-based Systems
KW - Dynamic Reconfiguration
KW - Self-Configuration
KW - Variability Models
UR - https://www.scopus.com/pages/publications/85164748368
U2 - 10.1007/978-3-031-35361-1_15
DO - 10.1007/978-3-031-35361-1_15
M3 - Conference contribution
AN - SCOPUS:85164748368
SN - 9783031353604
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 271
EP - 291
BT - Coordination Models and Languages - 25th IFIP WG 6.1 International Conference, COORDINATION 2023, Held as Part of the 18th International Federated Conference on Distributed Computing Techniques, DisCoTec 2023, Proceedings
A2 - Jongmans, Sung-Shik
A2 - Lopes, Antónia
PB - Springer Science and Business Media Deutschland GmbH
T2 - 25th IFIP WG 6.1 International Conference on Coordination Models and Language, COORDINATION 2023, held as part of the 18th International Federated Conference on Distributed Computing Techniques, DisCoTec 2023
Y2 - 19 June 2023 through 23 June 2023
ER -