Despite considerable technological advances for smart cities, they still face problems such as instability of cloud server connection, insecurity during data transmission, and slight deficiencies in TCP/IP network architecture. To address such issues, we propose a data-driven intelligence approach to security decisions under Named Data Networking (NDN) architecture for edge computing, taking into consideration factors that impact device entry in smart cities, such as device performance, load, Bluetooth signal strength, and scan frequency. Despite existing techniques for Order Preference by Similarity to Ideal Solution (TOPSIS)-based on entropy weights methods are improved and applied, there exist unstable decision results. Due to this, we propose a technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based on utility function and entropy weights, named UETOPSIS, where the corresponding utility function is applied according to the influence of each attribute on the decision, ensuring the stability of the ranking of decision results. We rely on an entropy-based weights mechanism to select a suitable master controller for the design of the multi-control protocol in the smart city system, and utilize a utility function to calculate the attribute values and then combine the normalized attribute values of utility numbers, starting by analyzing the main work of the controllers. Lastly, a prototype is developed for performance evaluation purposes. Experimental evaluation and analysis show that the proposed work has better authenticity and reliability than existing works and can reduce the workload of edge computing devices when forwarding data, with stability 24.7% higher than TOPSIS, significantly improving the performance and stability of system fault tolerance and reliability in smart cities, as the second-ranked controller can efficiently take over the work when a central controller fails or damaged.

尽管智慧城市在技术上取得了长足的进步，但仍然面临着云服务器连接不稳定、数据传输不安全、TCP/IP网络架构存在轻微缺陷等问题。为了解决这些问题，我们提出了一种数据驱动的智能方法，用于边缘计算的命名数据网络（NDN）架构下的安全决策，同时考虑影响设备进入智慧城市的因素，例如设备性能、负载、蓝牙信号强度和扫描频率。尽管对现有基于熵权法的理想解相似顺序偏好(TOPSIS)技术进行了改进和应用，但仍存在决策结果不稳定的问题。为此，我们提出了一种基于效用函数和熵权的理想解相似度排序偏好（TOPSIS）技术，称为UETOPSIS，根据每个属性对决策的影响应用相应的效用函数，确保决策结果排名的稳定性。我们依靠基于熵的权重机制来选择合适的主控制器来设计智慧城市系统中的多控制协议，并利用效用函数来计算属性值，然后组合效用数的归一化属性值，首先分析控制器的主要工作。最后，开发原型用于性能评估目的。实验评估和分析表明，所提出的工作比现有工作具有更好的真实性和可靠性，可以减少边缘计算设备转发数据时的工作量，稳定性比TOPSIS提高24.7%，显着提高了系统容错性和可靠性的性能和稳定性在智慧城市中，当中央控制器出现故障或损坏时，第二级控制器可以有效地接管工作。