An intermittent connectivity experience node by paradigm of opportunistic forwarding has been proposed to serve emerging wireless networking applications transmit messages to a distant destination for given delay bound, disjoined parts of the network exchange information by nodes broker to exploit node mobility. Forwarding decision is made by main challenge of opportunistic forwarding relays the best chosen cumulative probability within the delay bound of destination. The Bee Colony algorithm performs a kind of neighborhood search to solve this issue at recent work combined with global search used for both combined optimization and continuous optimization. Choosing initial centroid clusters is the problem for OFPC affects the efficiency of algorithm. The initial centroids for clusters are found to introduce by Bee Colony algorithm. A new opportunistic forwarding scheme is designed after finding the initial centroid, partial centrality with opportunistic forwarding (OFPC), and theoretically quantifies the partial centrality influence on the data forwarding performance using Bee colony optimization. Bee Colony optimization creates multi agent system capable to successfully solved difficult combinatorial optimization problem as the basic idea. Different TTL requirements are epidemic by applying our scheme on three real opportunistic networking scenarios, our extensive evaluations show that our scheme achieves significantly better mean delivery delay and cost compared to the state-of-the-art works, achieve delivery ratios sufficiently closer. The OFPC outperforms other solutions overall with extending shows the evaluation result, especially in terms of mean delivery delay and cost.

Opportunistic Forwarding with Partial Centrality, Bee Colony algorithm, clustering, opportunistic networking scenarios, Decayed Aggregation Graph

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