Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms


This work presents the application of a parallel cooperative optimization approach to the broadcast operation in mobile ad-hoc networks (MANETS). The optimization of the broadcast operation implies satisfying several objectives simultaneously, so a multi-objective approach has been designed. The optimization lies oil searching the best configurations of the DFCN broadcast protocol for a given MANET scenario. The cooperation of a team of multi-objective evolutionary algorithms has been performed with a novel optimization model. Such model is a hybrid parallel algorithm that combines a parallel island-based scheme with a hyperheuristic approach. Results achieved by the algorithms in different stages of the search process are analyzed in order to grant more computational resources to the most suitable algorithms. The obtained results for a MANETS scenario, representing a mall, demonstrate the validity of the new proposed approach.