机会网络自私节点的Bertrand博弈与激励机制研究

在真实的网络环境中，很多节点可能是自私的，它们不愿意牺牲自己的资源为其他节点转发消息。针对这种情况，提出一种基于博弈论的激励机制，可以激励节点与其他节点相互合作。该机制为二阶段激励，激励节点接收消息以协助其他节点转发，同时激励节点转发更多的消息。把源节点与中继节点之间的竞争与合作模型化为Bertrand（伯特兰德）博弈，定义了源节点和中继节点的效用函数。求解了源节点的最佳定价策略和中继节点最佳的转发计划，验证了源节点与中继节点之间存在唯一的纳什均衡。模拟仿真结果表明提出的激励机制能够鼓励自私节点参与合作，能提高路由算法的传递率，同时降低了消息传递延迟。与基于声誉的激励机制相比，所提激励机制能使消息传递成功率提高31.4%、平均时延降低9.7%。

Research on Bertrand Game and Incentive Mechanism for Selfish Nodes in Opportunistic Networks

In a real environment, many nodes may be selfish and unwilling to sacrifice their own resources to forward messages for other nodes. In this case, an incentive mechanism based on game theory to encourage the cooperation between nodes is proposed. This incentive provides two-stage incentives to nodes, which incentives node receives the message to assist other nodes to forward, while motivating the node to forward more messages. It models the cooperation between the source and the relay node as Bertrand game, and the utility functions of the source and the relay node are defined. It solves the best pricing scheme for the source node and the best forwarding plan for the relay node, and the Nash equilibrium is existed and unique between source node and relay node. The simulation results show that the proposed incentive mechanism can encourage the cooperation between selfish nodes, and improve the performance of routing algorithm in terms of delivery rate and delay. Compared with reputation-based incentive mechanism, the proposed mechanism has the success rate of message transmission increased by 31.4% and average delay decreased by 9.7%.