Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
