SAAM: A self-adaptive aggregation mechanism for autonomous management systems

In this paper, we propose a decentralized Self-Adaptive Aggregation Mechanism (SAAM) that adapts itself to the supporting network operational behavior by dynamically selecting the best aggregation approach to use. SAAM is based on (1) a fuzzy-based model that estimates the cost and performance of each aggregation scheme and (2) Multiple Attribute Decision Making (MADM) to make decisions on the best approach to use in this context. We validate SAAM by evaluating its fuzzy model and adaptation cost, and by comparing its utility to the one of existing situated and global schemes.