The parameters used in the cluster simulation.

The integration of the Internet of Things (IoT) in healthcare, especially for people with diabetes, allows for constant health monitoring. This means that doctors can watch over patients’ health more closely, making sure they catch any issues early on. With this technology, healthcare workers can be more accurate and effective when keeping an eye on how patients are doing. This not only helps in keeping track of patients’ health in real-time but also makes the whole process more reliable and efficient.By implementing appropriate routing techniques, the transmission of diabetic patients’ data to medical centers will facilitate real-time and timely responses from healthcare professionals. The grasshopper optimization algorithm is employed in the proposed approach to cluster network nodes, resulting in the formation of a network tree that facilitates the establishment of connections between the cluster head and the base station. After identifying the cluster head and establishing the clusters, the second stage of routing is implemented by employing the Harris Hawks optimization algorithm. This algorithm ensures that the data pertaining to diabetic patients is transmitted to the treatment centers and hospitals with minimal delay. For node routing, the optimal next step is selected based on the parameters such as the residual energy of the node, the ratio of delivered data packages, and the number of the neighbors of the node. To continue, first, the MATLAB software is utilized to simulate the proposed method, and then, it is compared with other similar methods. This comparison is conducted based on various parameters, including delay, energy consumption, network throughput, and network lifespan. Compared to other methods, the proposed method demonstrates a significant 33% improvement in the average point-to-point delay parameter in the subsequent iterations or rounds.物联网（Internet of Things, IoT）在医疗领域的集成应用，尤其针对糖尿病患者，可实现持续性健康监测。这意味着医护人员可更为细致地监护患者健康，确保尽早发现各类健康异常。借助该技术，医护人员在监测患者状况时可兼具更高的准确性与工作效率，此举不仅可实现患者健康的实时追踪，还能优化整体医疗流程，提升其可靠性与运行效率。通过应用适配的路由技术，将糖尿病患者的健康数据传输至医疗中心，可助力医护人员做出实时且及时的响应。所提方案采用蚱蜢优化算法（Grasshopper Optimization Algorithm）对网络节点进行聚类，进而构建网络树结构，以完成簇头与基站间的连接搭建。在完成簇头识别与簇群构建后，方案的第二阶段路由环节借助哈里斯鹰优化算法（Harris Hawks Optimization Algorithm）完成。该算法可确保糖尿病患者的相关数据以最小延迟传输至诊疗中心与医院。在节点路由阶段，将依据节点剩余能量、已交付数据包比率以及节点邻居节点数量等参数，选取最优下一跳节点。后续首先采用MATLAB软件对所提方案进行仿真，随后将其与其他同类方案开展对比实验。本次对比将基于延迟、能耗、网络吞吐量以及网络生命周期等多项参数展开。相较于其他同类方案，所提方案在后续迭代轮次中的平均端到端延迟参数实现了33%的显著改善。