WMNs中基于节点可信度的机会路由改进算法

机会路由提高了WMNs的可靠性和吞吐量,但同时由于节点候选集中存在恶意节点,导致网络性能下降。对于如何及时识别、隔离网络中的恶意节点的问题,建立了一种节点可信度评估模型。基于贝叶斯网络算法,考虑到非恶意因素带来的网络异常行为,引入不确定交互因子,改进了直接信任的评估方法,利用熵为信任值的计算和更新分配权重。引入反映节点真实参与度的行为积极因子并结合信任值得出节点的可信度,对可信度处于待定状态的节点进行未来可信度的预测,以甄别潜在的恶意节点。最后将该模型应用于机会路由ExOR中,提出了一种基于节点可信度的机会路由算法BTOR。实验结果表明,该算法可以有效检测恶意节点,在各项性能指标上比原路由算法更具优势。

Improved Opportunistic Routing Algorithm Based on Node Trustworthiness for WMNs

Opportunistic routing improves the reliability and throughput of WMNs,at the same time,the network performance degrades due to the existence of malicious nodes in candidate set.In order to solve the problem that how to timely identify and isolate malicious nodes,a node trustworthiness evaluation model was proposed.Based on Bayesian Networks Algorithm,considering the abnormal behavior caused by non-invasive factors,the uncertainty interaction factor is introduced to improve the estimate method of direct trust,and entropy is used to assign weights for calculation and update of trust value.The trustworthiness of the node is obtained by combining the trust value and the positive factor of behavior which is introduced to reflect the real participation of nodes,and the future trustworthiness for those nodes whose trustworthiness is uncertain is predicted to identify potential malicious nodes.Finally,the model was applied to ExOR and an opportunistic routing algorithm based on trustworthiness BTOR was proposed.The experimental results show that the algorithm can effectively detect the malicious nodes,and has advantages than original routing algorithms in performances.