In recent decades, Sensor nodes (SNs) are used in numerous uses of heterogeneous wireless sensor networks (HWSNs) to obtain a variety of sensing data sources. Sink mobility shows a significant part in the enhancement of sensor system execution, energy utilization, and lifetime. To manage sink mobility, rendezvous points (RPs) are introduced where some SNs are chosen as RPs, and the non-RP nodes convey the information to the cluster heads (CHs). The CHs then forward their information to the nearby RPs. To determine the set of RPs and travelling path of mobile sinks (MSs) that visits these RPs is quite challenging. This work presents an energy-efficient SOSS based routing method that depends on RPs and multiple MSs in HWSNs. At first, all the heterogeneous nodes are distributed into the number of clusters using mean shift clustering (MSC). Then, the Bald eagle search (BES) algorithm is used for an optimal selection of CHs whereas multiple MS is employed for effective data gathering. The use of multiple MSs can enhance the data collection efficiency and decreases the energy utilization for HWSNs. Finally, the hybrid seagull optimization and salp swarm (SOSS) algorithm is used to find the RPs and travelling routes of MS. The entire simulation work of the heterogeneous network is simulated in the NS2 platform. The simulation outcomes display that the suggested method provides superior performance in HWSN than other current routing protocols.

近几十年来，传感器节点 (SN) 被广泛用于异构无线传感器网络 (HWSN) 以获取各种传感数据源。Sink 移动性在增强传感器系统执行、能量利用和寿命方面发挥了重要作用。为了管理宿移动性，引入了集合点 (RP)，其中一些 SN 被选为 RP，并且非 RP 节点将信息传送到簇头 (CH)。然后 CH 将它们的信息转发给附近的 RP。确定访问这些 RP 的移动接收器 (MS) 的 RP 集和行进路径非常具有挑战性。这项工作提出了一种基于 SOSS 的节能路由方法，该方法依赖于 HWSN 中的 RP 和多个 MS。首先，所有异构节点使用均值漂移聚类（MSC）分配到多个簇中。然后，白头鹰搜索 (BES) 算法用于 CH 的最佳选择，而多个 MS 用于有效的数据收集。使用多个 MS 可以提高数据收集效率并降低 HWSN 的能源利用率。最后，使用混合海鸥优化和salp swarm（SOSS）算法来寻找MS的RP和行进路线。异构网络的整个仿真工作在NS2平台上进行仿真。仿真结果表明，所建议的方法在 HWSN 中提供了比其他当前路由协议更优越的性能。最后，使用混合海鸥优化和salp swarm（SOSS）算法来寻找MS的RP和行进路线。异构网络的整个仿真工作在NS2平台上进行仿真。仿真结果表明，所建议的方法在 HWSN 中提供了比其他当前路由协议更优越的性能。最后，使用混合海鸥优化和salp swarm（SOSS）算法来寻找MS的RP和行进路线。异构网络的整个仿真工作在NS2平台上进行仿真。仿真结果表明，所建议的方法在 HWSN 中提供了比其他当前路由协议更优越的性能。