A probabilistic approach for managing mobile ad-hoc networks

A pure management approach where all the nodes are managed at any time is too strict for mobile ad-hoc networks. Instead of addressing the management of the whole network, we propose a probabilistic scheme where only a subset of nodes is managed in order to provide a light-weight and efficient management. These nodes are determined based on their network behavior to favor subsets of well connected and network participating nodes. With respect to such a selective management scheme, we derive probabilistic guarantees on the percentage of nodes to be managed. Our contribution is centered on a distributed self-organizing management algorithm at the application layer, its efficient deployment into a management architecture and on a comprehensive simulation study. We will show how to organize the management plane by extracting spatio-temporal components and by selecting manager nodes with several election mechanisms based on degree centrality, eigenvector centrality and K-means paradigm.