NeTS: Small: Timely Updating: Principles and Applications

随着网络物理系统的出现，实时状态更新已成为一种重要且无处不在的通信形式。使用车辆状态消息、来自计算机、家庭和办公室的安全报告以及来自远程控制系统的监控视频的应用程序需要尽可能及时地更新状态;然而，这通常受到有限网络资源的限制。 这种紧张关系导致了基于信息时代（AoI）的新性能指标的引入，这些指标捕获了一个人对系统或过程的知识的及时性。基于AoI的网络服务设施和传感器更新策略的优化已经产生了新的甚至令人惊讶的结果，最终将提高车辆安全警告系统的可靠性，减少视频监控所需的带宽，并提高传感器网络的能源效率。 虽然需要继续分析基本模式和方法，但也需要结合具体应用研究《农产品价格协定》的优点。 因此，该项目有四个组成部分：（1）状态相关更新：更新提交过程将被优化的来源，是受能源和电力的限制，通过随时间变化的服务设施发送更新。 (2)状态更新多路访问：新协议将被设计用于通过共享随机访问信道发送更新的无线传感器。 (3)实时通用数据压缩：对于具有未知统计量的离散随机信源，通用流信源编码系统的AoI性能将被表征。 (4)远程视频更新：AoI指标将用于研究H.264视频帧应如何交付给基于机器的监控。 项目的前三个组成部分将致力于基本问题领域的新数学见解，方法和算法。第四个组成部分，视频更新，表示这些方法和算法将被应用到的应用领域。

With the emergence of cyber-physical systems, real-time status updates have become an important and ubiquitous form of communication. Applications that employ vehicular status messages, security reports from computers, homes, and offices, and surveillance video from remote-controlled systems need status updates to be as timely as possible; however, this is typically constrained by limited network resources. This tension has led to the introduction of new performance metrics based on the Age of Information (AoI) that capture how timely is one's knowledge of a system or process. AoI-based optimization of both the network service facility and the senders' updating policies has yielded new and even surprising results that ultimately will increase the reliability of vehicular safety warning systems, reduce the bandwidth needed for video monitoring, and increase the energy efficiency of sensor networks.Much of this recent work has been directed toward an analytic understanding of AoI using mathematical models. While the analysis of basic models and methods needs to continue, the merits of AoI also need to be studied in the context of specific applications. Thus, this project has four components: (1) State Dependent Updating: the update submission process will be optimized for a source that is subject to energy and power constraints in sending updates through a time-varying service facility. (2) Status Update Multiple Access: new protocols will be designed for wireless sensors sending updates through a shared random access channel. (3) Real-time Universal Data Compression: for a discrete random source with unknown statistics, the AoI performance of universal streaming source coding systems will be characterized. (4) Remote Video Updating: the AoI metric will be used to study how H.264 video frames should be delivered for machine-based surveillance. The first three project components will aim for new mathematical insights, methods and algorithms in fundamental problem areas. The fourth component, video updating, represents an application area to which these methods and algorithms will be applied.