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Analysing connectivity patterns and centrality metrics for opportunistic networks

Network centrality measures are used to identify important and influential nodes in any network. Several centrality measures are proposed in literature for static networks however these measures cannot be used for routing purpose in opportunistic networks as opportunistic networks are dynamic in nature. Opportunistic networks utilise pocket switching for routing messages where each device attempts to forward its messages to a suitable next node. Appropriate decision making for the selection of the forwarder node is crucial for the performance of a routing protocol in opportunistic networks. In any opportunistic network, some node play more important role in the routing process than the rest of the network. In this paper, we have analysed metrics that can be used to simplify the centrality measure computation in opportunistic networks. We have investigated the relationship between these node (ego) characteristics with centrality measures that are computed using novel network transformations. The aim of the transform mechanisms is to aggregate the link between any two nodes in a way that strongly relates the nodes which frequently come in contact with each other. Our experiment show that ego characteristics can be used to estimate centrality measures for dense opportunistic networks.