The most famous wireless sensor networks is one of the cheapest and rapidly evolving networks in modern communication. It can be used to sense various substantial and environmental specifications by providing cost-effective sensor devices. The development of these sensor networks is exploited to provide an energy-efficient weighted clustering method to increase the lifespan of the network. We propose a novel energy-efficient method, which utilizes the brainstorm algorithm in order to adopt the ideal cluster head (CH) to reduce energy draining. Furthermore, the effectiveness of the BrainStorm Optimization (BSO) algorithm is enhanced with the incorporation of the modified teacher–learner optimized (MTLBO) algorithm with it. The modified BSO–MTLBO algorithm can be used to attain an improved throughput, network lifetime, and to reduce the energy consumption by nodes and CH, death of sensor nodes, routing overhead. The performance of our proposed work is analyzed with other existing approaches and inferred that our approach performs better than all the other approaches.

中文翻译：

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基于混合BSO-TLBO优化模型的WSN节能集群路由协议

最著名的无线传感器网络是现代通信中最便宜且发展迅速的网络之一。通过提供具有成本效益的传感器设备，它可用于感测各种实质性和环境规范。这些传感器网络的发展被利用来提供一种节能的加权聚类方法，以增加网络的寿命。我们提出了一种新颖的节能方法，该方法利用头脑风暴算法来采用理想的簇头（CH）来减少能量消耗。此外，头脑风暴优化 (BSO) 算法的有效性随着改进的教师-学习者优化 (MTLBO) 算法的结合而得到增强。修改后的 BSO-MTLBO 算法可用于提高吞吐量、网络寿命、并减少节点和CH的能量消耗、传感器节点的死亡、路由开销。我们提出的工作的性能与其他现有方法进行了分析，并推断出我们的方法比所有其他方法表现更好。