With the applications of Internet of Things (IoT) for smart cities, the real-time performance for a large number of network packets is facing serious challenge. Thus, how to improve the emergency response has become a critical issue. However, traditional packet scheduling algorithms cannot meet the requirements of the large-scale IoT system for smart cities. To address this shortcoming, this paper proposes EARS, an efficient data-emergency-aware packet scheduling scheme for smart cities. EARS describes the packet emergency information with the packet priority and deadline. Each source node informs the destination node of the packet emergency information before sending the packets. The destination node determines the packet scheduling sequence and processing sequence according to emergency information. Moreover, this paper compares EARS with a first-come, first-served, multilevel queue algorithm and a dynamic multilevel priority packet scheduling algorithm. Simulation results show that EARS outperforms these previous scheduling algorithms in terms of packet loss rate, average packet waiting time, and average packet end-to-end delay.

中文翻译：

---

智慧城市中物联网的数据紧急感知调度方案

随着物联网（IoT）在智能城市中的应用，大量网络数据包的实时性能面临着严峻的挑战。因此，如何改善应急响应已成为关键问题。然而，传统的分组调度算法无法满足智能城市大规模物联网系统的要求。为了解决这个缺点，本文提出了EARS，这是一种用于智慧城市的高效的数据紧急感知数据包调度方案。EARS用数据包优先级和截止日期描述数据包紧急信息。每个源节点在发送数据包之前将数据包紧急信息通知给目标节点。目的节点根据紧急信息确定报文的调度顺序和处理顺序。而且，本文将EARS与先来先服务的多级队列算法和动态多级优先级数据包调度算法进行了比较。仿真结果表明，在丢包率，平均数据包等待时间和平均数据包端到端延迟方面，EARS优于以前的调度算法。