Fog computing integrates cloud and edge resources. According to an intelligent and decentralized method, this technology processes data generated by IoT sensors to seamlessly integrate physical and cyber environments. Internet of Things uses wireless and smart objects. They communicate with each other, monitor the environment, collect information, and respond to user requests. These objects have limited energy resources since they use batteries to supply energy. Also, they cannot replace their batteries. As a result, the network lifetime is limited and short. Thus, reducing energy consumption and accelerating the data transmission process are very important challenges in IoT networks to reduce the response time. In the data transmission process, selecting an appropriate cluster head node is very important because it can reduce the delay when sending data to the fog. In this paper, cluster head nodes are selected based on several important criteria such as distance, residual energy, received signal strength, and link expiration time. Then, objects send the processed data to the server hierarchically through a balanced tree. The simulation results show that the proposed method outperforms the energy-efficient centroid-based routing protocol (EECRP) and the Emergency Response IoT based on Global Information Decision (ERGID) in terms of packet delivery rate, delay, response time, and network lifetime.

翻译：雾计算整合了云与边缘资源。该技术通过智能且去中心化的方式，处理物联网传感器生成的数据，实现物理与网络环境的无缝融合。物联网采用无线智能设备，这些设备相互通信、监测环境、收集信息并响应用户请求。由于使用电池供电且无法更换，这些设备的能源资源有限，导致网络生命周期短暂受限。因此，降低能耗与加速数据传输成为物联网网络中减少响应时间的核心挑战。在数据传输过程中，簇头节点的选取至关重要，因其能减少数据发送至雾层的延迟。本文基于距离、剩余能量、接收信号强度及链路失效时间等关键指标选取簇头节点，并通过平衡树将处理后的数据分层传输至服务器。仿真结果表明，所提方法在数据包投递率、延迟、响应时间及网络生命周期方面均优于能量高效的质心路由协议（EECRP）和基于全局信息决策的应急响应物联网方案（ERGID）。