Wireless sensor networks (WSNs) have gained much attention in public and research communities due to their incredible capabilities and ever-growing range of applications. The WSN is equipped with a specialized transducer that adds the sensing services to IoT. This equipment is limited to battery and resource capacity, which introduces many challenges to academia and industry. Hence WSN has to be utilized in an energy-efficient manner to maximize the network’s lifetime while providing a precise QoS guarantee. QoS is an essential issue in many IoT applications such as environmental monitoring, smart cities, weather monitoring, animal tracking, disaster management, bio-medical applications. An optimal clustering technique for WSN, which includes the formation of clusters, and cluster head (CH) selection, can significantly improve the QoS to increase the lifespan of a WSN. This paper proposes a Grey wolf optimization-based cluster head selection technique for WSN considering distinct factors like energy level of the node, node degree, sink distance, intracluster distance, and priority factor. This paper also addresses the routing through QoS aware relay node selection for effective and reliable inter-cluster routing from CHs to Base station (BS). The proposed technique is simulated and evaluated based on the Quality of Service (QoS) parameters viz. residual energy, stability period, throughput, network lifetime, and delay. The proposed techniques improve the overall network performance by 10.00%, 23.75%, and 54.54% corresponding to ESO, GECR, and LEACH. Hence, the study infers that the protocol is well suited to design WSNs in IoT applications.

无线传感器网络（WSN）由于其不可思议的功能和不断增长的应用范围而在公众和研究界引起了广泛关注。WSN配备了专门的传感器，可将传感服务添加到物联网中。该设备限于电池和资源容量，这给学术界和工业界带来了许多挑战。因此，必须以高能效的方式利用WSN，以在提供精确的QoS保证的同时最大程度地延长网络的使用寿命。QoS是许多物联网应用程序中的重要问题，例如环境监控，智慧城市，天气监控，动物跟踪，灾难管理，生物医学应用程序。WSN的最佳集群技术，包括集群的形成和集群首部（CH）的选择，可以显着提高QoS，以延长WSN的使用寿命。针对节点的能量水平，节点度，汇聚距离，集群内距离和优先级因子等不同因素，本文提出了一种基于灰狼优化的WSN簇头选择技术。本文还介绍了通过QoS感知中继节点选择进行的路由，以实现从CH到基站（BS）的有效而可靠的集群间路由。基于服务质量（QoS）参数viz对所提出的技术进行仿真和评估。剩余能量，稳定期，吞吐量，网络寿命和延迟。所提出的技术将总体网络性能提高了10.00％，23.75％和54.54％，分别对应于ESO，GECR和LEACH。因此，研究推断该协议非常适合在物联网应用中设计WSN。