论文标题
IoT上行链路网络中的信息新鲜度的时空框架
A Spatiotemporal Framework for Information Freshness in IoT Uplink Networks
论文作者
论文摘要
及时消息传递是物联网（IoT）和网络物理系统的关键推动力，可支持广泛的上下文依赖性应用程序。传统的时间相关指标（例如延迟）无法表征系统更新的及时性或从应用程序的角度捕获信息的新鲜度。信息年龄（AOI）是一个时代。在过去几年中，新的新鲜度衡量新鲜度。在预见的大规模和密集的物联网网络中，需要对AOI进行临时时间（即队列意识）和空间（即相互干扰）表征。在这项工作中，我们提供了一个时空框架，该框架捕获了大型IoT上行链路网络的峰值AOI。为此，本文用Bernoulli上行链路流量量化了大型蜂窝网络的峰值AOI。进行仿真结果以验证所提出的模型并显示交通负荷和解码阈值的效果。洞察力是为了表征网络稳定边界和网络中位置依赖性性能。
Timely message delivery is a key enabler for Internet of Things (IoT) and cyber-physical systems to support wide range of context-dependent applications. Conventional time-related metrics, such as delay, fails to characterize the timeliness of the system update or to capture the freshness of information from application perspective. Age of information (AoI) is a time.evolving measure of information freshness that has received considerable attention during the past years. In the foreseen large scale and dense IoT networks, joint temporal (i.e., queue aware) and spatial (i.e., mutual interference aware) characterization of the AoI is required. In this work we provide a spatiotemporal framework that captures the peak AoI for large scale IoT uplink network. To this end, the paper quantifies the peak AoI for large scale cellular network with Bernoulli uplink traffic. Simulation results are conducted to validate the proposed model and show the effect of traffic load and decoding threshold. Insights are driven to characterize the network stability frontiers and the location-dependent performance within the network.
