EAGER: Collaborative Research: Fundamental Limits on Information Freshness

在物联网(IoT)、智能车载系统、无线通信反馈、环境监测、机器人网络以及网络物理系统的实时监控等各种网络化监控系统中，信息新鲜度都是至关重要的。此外，它在一些信息更新和数据分析应用程序中也很重要，包括金融交易、社交网络、众包、共识系统和在线学习。在所有这些应用中，过时的信息可能会导致错误的决策、不稳定的控制回路，甚至会危及安全。由于及时更新在这些和许多其他当代应用中是至关重要的，因此一个重要的问题是了解联网状态更新系统中信息新鲜度的基本限制。该项目将进一步加深我们对一般多来源/多监视器环境中信息新鲜度的基本限制的理解，并将制定实现这些限制的策略。该项目还包括本科生和研究生的研究经验。该项目的方法不同于以前在信息时代(AOI)的工作，它考虑了具有显式竞争的一般多源/多监视器网络，并使用图论中的技术在具有干扰约束的一般网络拓扑中研究AOI度量下的信息新鲜度。这种方法有望在具有一般拓扑的现实网络中带来新的见解。为了更好地理解AOI在显式竞争框架中的理论基础，研究计划被组织成三个相关的任务：(I)同时传输和网络编码，(Ii)广义信息映射和年龄加权，以及(Iii)大网络限制。所有这些任务的重点都是确定信息新鲜度的基本限制，并制定策略以在一般类别的无线和有线网络中接近或达到这些限制。这项拟议的工作将把AOI的显式竞争框架概括为丰富的、现实的一类问题设置，包括节点可以同时广播信息更新的设置，节点可以访问公共或相关信息的设置，以及某些信息比其他信息更关键的设置。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Information freshness is of critical importance in a variety of networked monitoring and control systems such as Internet of Things (IoT), intelligent vehicular systems, feedback in wireless communication systems, environmental monitoring, robotic networks, and real-time monitoring and control in cyber-physical systems. In addition it is important in several information-update and data analytics applications including financial trading, social networks, crowdsourcing, consensus systems, and online learning. In all these applications, stale information can lead to incorrect decisions, unstable control loops, and even compromises in safety and security. Since timely updates are critical in these and many other contemporary applications, an important problem is to understand the fundamental limits of information freshness in networked status update systems. This project will further our understanding of the fundamental limits of information freshness in general multi-source/multi-monitor settings, and will develop strategies to achieve these limits. The project also includes engaging research experiences for both undergraduate and graduate students.The approach in this project differs from prior work in age of information (AoI) by considering general multi-source/multi-monitor networks with explicit contention and using techniques from graph theory to study information freshness under the AoI metric in general network topologies with interference constraints. This approach is expected to lead to new insights in realistic networks with general topologies. The research plan is organized into three related tasks to better understand the theoretical foundations of AoI in the explicit contention framework: (i) simultaneous transmission and network coding, (ii) generalized information mappings and age weightings, and (iii) large-network limits. The focus in all of these tasks is on characterizing fundamental limits of information freshness and developing strategies to approach or achieve these limits in general classes of wireless and wired networks. The proposed work will generalize the explicit contention framework for AoI to a rich, realistic class of problem settings including settings where nodes can simultaneously broadcast information updates, settings where nodes have access to common or correlated information, and settings where certain information is more critical than other information.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.