Towards Self-Adaptive Management Frameworks: The Case of Aggregated Information Monitoring

Rafik Makhloufi (1) , Guillaume Doyen (1) , Grégory Bonnet (2) , Dominique Gaïti (1)

1 ERA - Environnement de Réseaux Autonomes
2 Equipe MAD - Laboratoire GREYC - UMR6072

In this paper, we propose a decentralized self-adaptive management framework that infers the current context of the hosting environment and dynamically decides what management strategy should be used in order to minimize the cost and maximize the performance of management. We investigate the use of this framework in the case of the aggregated information monitoring, where only one scheme (i.e. situated or global) is generally used for collecting aggregated information whatever the nature of the management information and its environment are. We propose a self-adaptive aggregation mechanism based on fuzzy logic, that estimates the cost and the performance of given aggregation schemes.

Domaines: Intelligence artificielle [cs.AI]; Système multi-agents [cs.MA]; Modélisation et simulation

Rafik Makhloufi, Guillaume Doyen, Grégory Bonnet, Dominique Gaïti. Towards Self-Adaptive Management Frameworks: The Case of Aggregated Information Monitoring. Proceedings of the 7th International Conference on Network and Service Management, Oct 2011, Paris, France. pp.1-5. ⟨hal-00951819⟩