A multi-criteria master nodes selection mechanism for knowledge dissemination in autonomic networks

Autonomic Networks represent a concept inspired by the biological world that aims at making a network independent of any human monitoring. To reach such autonomy, knowledge should be disseminated over the network, which remains an open problem. In fact, disseminating the knowledge over all nodes leads to a big overhead. That is why we need to select a subset of nodes in charge of knowledge management. A single criterion-based selection mechanism has been proposed in a previous work but such a mechanism seems to be very simplistic. In this paper, we present a new multi-criteria selection mechanism based on Pareto. The simulation results show that the proposed approach significantly improves performances compared to single criterion-based selection mechanism.