Abstract

Existing routing algorithms for Delay Tolerant Networks (DTNs) assume that nodes are willing to forward packets for others. In the real world, however, most people are socially selfish; i.e., they are willing to forward packets for nodes with whom they have social ties but not others, and such willingness varies with the strength of the social tie. Following the philosophy of design for user, we propose a Social Selfishness Aware Routing (SSAR) algorithm to cope with user selfishness and provide good routing performance in an efficient way. To select an effective forwarding node, SSAR considers both users’ willingness to forward and their contact opportunity, and derives a metric with mathematical modeling and machine learning techniques to measure the forwarding capability of the mobile nodes. Moreover, SSAR formulates the data forwarding process as a Multiple Knapsack Problem with Assignment Restrictions (MKPAR) to satisfy user demands for selfishness and performance. Trace-driven simulations show that SSAR allows users to maintain selfishness and achieves good routing performance with low transmission cost.

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