This study is to explore the smart city information (SCI) processing technology based on the Internet of Things (IoT) and cloud computing, promoting the construction of smart cities in the direction of effective sharing and interconnection. In this study, a SCI system is constructed based on the information islands in the smart construction of various fields in smart cities. The smart environment monitoring, smart transportation, and smart epidemic prevention at the application layer of the SCI system are designed separately. A multi-objective optimization algorithm for cloud computing virtual machine resource allocation method (CC-VMRA method) is proposed, and the application of the IoT and cloud computing technology in the smart city information system is further analysed and simulated for the performance verification. The results show that the multi-objective optimization algorithm in the CC-VMRA method can greatly reduce the number of physical servers in the SCI system (less than 20), and the variance is not higher than 0.0024, which can enable the server cluster to achieve better load balancing effects. In addition, the packet loss rate of the Zigbee protocol used by the IoT gateway in the SCI system is far below the 0.1% indicator, and the delay is less than 10 ms. Therefore, the SCI system constructed by this study shows low latency and high utilization rate, which can provide experimental reference for the later construction of smart city.

本研究旨在探索基于物联网（IoT）和云计算的智慧城市信息（SCI）处理技术，推动智慧城市建设朝着有效共享和互联互通的方向发展。本研究基于智慧城市各领域智慧建设中的信息孤岛构建SCI系统。SCI系统应用层的智能环境监测、智能交通、智能防疫是分开设计的。提出了一种云计算虚拟机资源分配方法（CC-VMRA方法）的多目标优化算法，并进一步分析和仿真了物联网和云计算技术在智慧城市信息系统中的应用，以进行性能验证。结果表明，CC-VMRA方法中的多目标优化算法可以大大减少SCI系统中物理服务器的数量（小于20），方差不高于0.0024，可以使服务器集群达到更好的负载均衡效果。此外，SCI系统中物联网网关使用的Zigbee协议丢包率远低于0.1%指标，时延小于10ms。因此，本研究构建的SCI系统表现出低延迟和高利用率，可为后期智慧城市建设提供实验参考。可以使服务器集群达到更好的负载均衡效果。此外，SCI系统中物联网网关使用的Zigbee协议丢包率远低于0.1%指标，时延小于10ms。因此，本研究构建的SCI系统表现出低延迟和高利用率，可为后期智慧城市建设提供实验参考。可以使服务器集群达到更好的负载均衡效果。此外，SCI系统中物联网网关使用的Zigbee协议丢包率远低于0.1%指标，时延小于10ms。因此，本研究构建的SCI系统表现出低延迟和高利用率，可为后期智慧城市建设提供实验参考。