Advancements in wireless communication technologies have facilitated the deployment of large-scale Wireless Sensor Networks (WSNs). Due to the constraint of associated battery power, various optimization structures have been proposed to enhance the lifetime of WSNs. In this article, the concept of supernodes is used along with Moth Flame Optimization algorithm to improve the lifetime of the heterogeneous WSNs. The Moth Flame Optimization algorithm is used to achieve the energy-efficient clustering and energy-aware routing. The performance of Moth Flame Optimization algorithm is compared with the other existing protocol, including Genetic Algorithm and Particle Swarm Optimization algorithm. The effects of varying populations of supernodes and sensor nodes on the network metrics are also analyzed here. The influence of the number of hops on the lifetime is also investigated considering two different positions of the base-station in WSNs.

无线通信技术的进步促进了大规模无线传感器网络（WSN）的部署。由于相关电池电量的限制，已提出了各种优化结构来延长WSN的寿命。在本文中，将超节点的概念与飞蛾火焰优化算法一起使用，以提高异构WSN的寿命。飞蛾火焰优化算法用于实现节能集群和节能路由。将飞蛾火焰优化算法的性能与其他现有协议进行了比较，包括遗传算法和粒子群优化算法。此处还分析了超节点和传感器节点数量的变化对网络指标的影响。