The named data networking is most promising content-centric network architecture which allows multipath and adaptive forwarding plane. In this paper, we propose maximum deviation-based optimal forwarding strategy (MDOF) using ordered weighted averaging operator. Interest forwarding is modeled as multi-attribute decision-making problem. Considering dynamic network changes, attribute weights are objectively assigned in real time to obtain the deviation of aggregate attribute values among forwarding interfaces. Interest forwarding decision is then based on the ranking of interfaces according to the maximum deviation. The proposed method is scalable as any network metrics can be integrated into ordered weighted averaging operator. Experiments show that optimal strategy achieves higher throughput, better load balance, and lower packet drop rate compared to default forwarding strategies.
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