RT Conference Proceedings
T1 Towards the model-based predictive performance analysis of Cloud adaptive systems with e-Motions (Trabajo en progreso)
A1 De Oliveira, Patricia
A1 Durán, Francisco
A1 Pimentel-Sánchez, Ernesto
K1 Lenguajes de programación
AB We use graph transformation to define an adaptive component model, what allows us to carry on predictive analyses on dynamic architectures through simulations. Specifically, we build on the e-Motions definition of the Palladio component model, and then specify adaptation mechanisms as generic adaptation rules. We illustrate our approach with rules modelling the increase in the number of CPU replicas used by a component, and the distribution of works between processors, reacting, respectively, to saturated queues or response time constraints violations. We evaluate alternative scenarios by analysing their performance, and discuss on its consequences in practice.
YR 2017
FD 2017
LK http://hdl.handle.net/10630/14304
UL http://hdl.handle.net/10630/14304
LA spa
NO P. de Oliveira, F. Durán, E. Pimentel. Towards the model-based predictive performance analysis of Cloud adaptive systems with e-Motions (Trabajo en progreso). Durán, F.  (Ed.), Actas de las XVII Jornadas de Programación y Lenguajes (PROLE 2017). La Laguna (Tenerife), 2017.
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026