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首页> 外文期刊>International Journal of Intelligent Systems >Secured cross-layer cross-domain routing in dense wireless sensor network: A new hybrid based clustering approach
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Secured cross-layer cross-domain routing in dense wireless sensor network: A new hybrid based clustering approach

机译：密集无线传感器网络中的安全跨层跨域路由：一种新的基于混合的聚类方法

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摘要

In wireless sensor network (WSN), increasing the network life span remains as a crucial challenge yet to be resolved. The modeling of effectual methods is necessary for conserving the scarce energy resources in WSN. To overcome such issues, cross-layer protocols are exploited, which concerns routing the messages with increased lifetime. This study introduces a new cross-layer design routing model under a clustering-based approach. More importantly, the cluster head is optimally selected by a new hybrid algorithm termed as moth flame integrated dragonfly algorithm. Moreover, the optimal selection of cluster head is carried out based on parameters such as energy consumption, delay, distance, throughput, security, and overhead. Finally, the supremacy of the presented model is proved over existing models in terms of alive node analysis and network lifetime analysis. The experimental outcomes show that the proposed algorithm for test case 3 has accomplished a higher value of 66.229, which is 29.07%, 13.33%, 26.36%, and 9.67% better than conventional ant lion optimisation approach, grouped grey wolf search optimisation, firefly replaced position update in da, and alpha wolf-assisted whale optimization algorithm, respectively, for median case scenario.
机译：在无线传感器网络（WSN）中，增加网络寿命仍然是尚未解决的至关重要挑战。有效方法的建模是为了节省WSN中的稀缺能量资源是必要的。为了克服这些问题，利用跨层协议，涉及通过增加的寿命来路由消息。本研究在基于聚类的方法下介绍了一种新的跨层设计路由模型。更重要的是，通过称为飞蛾集成蜻蜓算法的新的混合算法最佳地选择群集头。此外，基于诸如能量消耗，延迟，距离，吞吐量，安全性和开销的参数来执行群集头的最佳选择。最后，就活力节点分析和网络寿命分析而言，在现有模型中证明了所提出的模型的至上。实验结果表明，该试验案例3的算法实现了更高的66.229级，比传统的蚂蚁优化方法，分组灰狼搜索优化，萤火虫更新，比常规蚂蚁狮子优化方法更高，为66.229的值为66.229，这是29.07％，13.3％，26.36％和9.67％分别在DA和Alpha Wolf辅助鲸鲸优化算法中更新，用于中位数情况。

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