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A Credibility Evaluation Method in Opportunistic Networks

机译：机会网络中的可信度评估方法

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There are lots of misbehaving nodes in opportunistic networks which can cause severe performance downgrade. Those misbehaving nodes contains malicious nodes and selfish nodes. Selfish nodes don't cooperate in routing and forwarding. Malicious nodes drop data packets or forward lots of garbage packets hindering the normal process of data forwarding. In order to improve network performance, a credibility evaluation method is proposed in this paper, named FICT. According to the FICT, familiar degree, intimate degree and contribution degree are defined to describe the social attributes of nodes. We use the number of contacts, connect time and PLR to calculate the value of the credibility of nodes. Just when the value of credibility is greater than or equal to the threshold, the node is selected to forward data packets. We performed simulation experiments with FICT method on the ONE. The simulation results show that by using the FICT method, the success rate of message delivery increases and the average latency of message delivery reduces. Especially when the number of misbehaving nodes becomes large, the FICT method can improve the performance of the networks significantly.
机译：机会网络中存在许多行为异常的节点，这可能会导致严重的性能降级。这些行为异常的节点包含恶意节点和自私节点。自私的节点在路由和转发中不合作。恶意节点会丢弃数据包或转发大量垃圾包，从而阻碍正常的数据转发过程。为了提高网络性能，本文提出了一种可信度评估方法，称为FICT。根据FICT，定义了熟悉度，亲密度和贡献度来描述节点的社会属性。我们使用联系数，连接时间和PLR来计算节点可信度的值。仅当可信度值大于或等于阈值时，才选择该节点转发数据包。我们用FICT方法对ONE进行了仿真实验。仿真结果表明，采用FICT方法，可以提高消息传递的成功率，减少消息传递的平均等待时间。尤其是当行为异常的节点数量变多时，FICT方法可以显着提高网络性能。

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