本文選題：WMNs + 機(jī)會(huì)路由　； 參考：《計(jì)算機(jī)科學(xué)》2017年08期

【摘要】：機(jī)會(huì)路由提高了WMNs的可靠性和吞吐量,但同時(shí)由于節(jié)點(diǎn)候選集中存在惡意節(jié)點(diǎn),導(dǎo)致網(wǎng)絡(luò)性能下降。對(duì)于如何及時(shí)識(shí)別、隔離網(wǎng)絡(luò)中的惡意節(jié)點(diǎn)的問題,建立了一種節(jié)點(diǎn)可信度評(píng)估模型�；谪惾~斯網(wǎng)絡(luò)算法,考慮到非惡意因素帶來的網(wǎng)絡(luò)異常行為,引入不確定交互因子,改進(jìn)了直接信任的評(píng)估方法,利用熵為信任值的計(jì)算和更新分配權(quán)重。引入反映節(jié)點(diǎn)真實(shí)參與度的行為積極因子并結(jié)合信任值得出節(jié)點(diǎn)的可信度,對(duì)可信度處于待定狀態(tài)的節(jié)點(diǎn)進(jìn)行未來可信度的預(yù)測,以甄別潛在的惡意節(jié)點(diǎn)。最后將該模型應(yīng)用于機(jī)會(huì)路由ExOR中,提出了一種基于節(jié)點(diǎn)可信度的機(jī)會(huì)路由算法BTOR。實(shí)驗(yàn)結(jié)果表明,該算法可以有效檢測惡意節(jié)點(diǎn),在各項(xiàng)性能指標(biāo)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(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院;
【基金】：國家自然科學(xué)基金項(xiàng)目(60673185,61073197)資助
【分類號(hào)】：TN929.5

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本文編號(hào)：1926316