本文選題：WMNs + 機會路由�。� 參考：《計算機科學》2017年08期

【摘要】：機會路由提高了WMNs的可靠性和吞吐量,但同時由于節(jié)點候選集中存在惡意節(jié)點,導致網絡性能下降。對于如何及時識別、隔離網絡中的惡意節(jié)點的問題,建立了一種節(jié)點可信度評估模型。基于貝葉斯網絡算法,考慮到非惡意因素帶來的網絡異常行為,引入不確定交互因子,改進了直接信任的評估方法,利用熵為信任值的計算和更新分配權重。引入反映節(jié)點真實參與度的行為積極因子并結合信任值得出節(jié)點的可信度,對可信度處于待定狀態(tài)的節(jié)點進行未來可信度的預測,以甄別潛在的惡意節(jié)點。最后將該模型應用于機會路由ExOR中,提出了一種基于節(jié)點可信度的機會路由算法BTOR。實驗結果表明,該算法可以有效檢測惡意節(jié)點,在各項性能指標上比原路由算法更具優(yōu)勢。
[Abstract]:Opportunistic routing improves the reliability and throughput of WMNs, but at the same time due to the presence of malicious nodes in the candidate set of nodes, the network performance is degraded. For the problem of how to identify and isolate the malicious nodes in the network in time, a model for evaluating the credibility of the nodes is established. Based on Bayesian network algorithm, considering the network abnormal behavior caused by non-malicious factors, the uncertain interaction factor is introduced, and the evaluation method of direct trust is improved. Entropy is used to calculate and update the trust value to assign weight. In order to identify the potential malicious nodes, a positive behavioral factor reflecting the degree of real participation of nodes is introduced, and the credibility of the nodes is worth the trust to predict the future credibility of the nodes in the state to be determined in order to identify the potential malicious nodes. Finally, the model is applied to opportunistic routing ExOR, and an opportunistic routing algorithm based on node credibility is proposed. Experimental results show that the algorithm can detect malicious nodes effectively and has more advantages than the original routing algorithm in terms of performance.
【作者單位】： 南京工業(yè)大學計算機科學與技術學院;
【基金】：國家自然科學基金項目(60673185,61073197)資助
【分類號】：TN929.5

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1 康松林;李瓊;周玖玖;;信譽模型在WMNs異常節(jié)點檢測中的應用[J];科學技術與工程;2012年20期

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本文編號：1926316