Natesan Gobi, Konda Srinivas, de Prado Rocío Pérez, Wozniak Marcin
Department of Computer Science and Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi 642003, Tamilnadu, India.
Department of Data Science, CMR Technical Campus, Hyderabad 501401, Telangana, India.
Sensors (Basel). 2022 Aug 25;22(17):6405. doi: 10.3390/s22176405.
In recent times, Wireless Sensor Networks (WSNs) are becoming more and more popular and are making significant advances in wireless communication thanks to low-cost and low-power sensors. However, since WSN nodes are battery-powered, they lose all of their autonomy after a certain time. This energy restriction impacts the network's lifetime. Clustering can increase the lifetime of a network while also lowering energy use. Clustering will bring several similar sensors to one location for data collection and delivery to the Base Station (BS). The Cluster Head (CH) uses more energy when collecting and transferring data. The life of the WSNs can be extended, and efficient identification of CH can minimize energy consumption. Creating a routing algorithm that considers the key challenges of lowering energy usage and maximizing network lifetime is still challenging. This paper presents an energy-efficient clustering routing protocol based on a hybrid Mayfly-Aquila optimization (MFA-AOA) algorithm for solving these critical issues in WSNs. The Mayfly algorithm is employed to choose an optimal CH from a collection of nodes. The Aquila optimization algorithm identifies and selects the optimum route between CH and BS. The simulation results showed that the proposed methodology achieved better energy consumption by 10.22%, 11.26%, and 14.28%, and normalized energy by 9.56%, 11.78%, and 13.76% than the existing state-of-art approaches.
近年来，无线传感器网络（WSNs）越来越受欢迎，由于低成本和低功耗传感器，在无线通信方面取得了重大进展。然而，由于WSN节点由电池供电，经过一定时间后它们会失去所有自主性。这种能量限制会影响网络的寿命。聚类可以增加网络的寿命，同时还能降低能源消耗。聚类将把几个相似的传感器带到一个位置进行数据收集并传送到基站（BS）。簇头（CH）在收集和传输数据时消耗更多能量。延长WSNs的寿命，高效识别簇头可以将能耗降至最低。创建一种考虑降低能源使用和最大化网络寿命等关键挑战的路由算法仍然具有挑战性。本文提出了一种基于混合蜉蝣 - 鹰优化（MFA - AOA）算法的节能聚类路由协议，用于解决WSNs中的这些关键问题。采用蜉蝣算法从节点集合中选择最优簇头。鹰优化算法识别并选择簇头与基站之间的最优路由。仿真结果表明，与现有的先进方法相比，所提出的方法在能耗方面分别提高了10.22%、11.26%和14.28%，在归一化能量方面分别提高了9.56%、11.78%和13.76%。
