CIF: Small: Timing Optimization Over Random Network Asynchrony - Theory And Distributed Algorithms

推动21世纪技术革命的一股关键力量是不断加速部署更强大但物理上更小的计算/传感设备，这些设备通过新一代无线网络持续且交互地连接。人们有兴趣支持每平方公里高达100万台设备的密度，一旦实现，将实现成倍增长的许多创新，进一步改变现代社会的面貌。支持如此大规模的机器类型通信的一个重大挑战是，现代无线网络在提供高吞吐量和广泛覆盖的同时，不可避免地容易受到随机延迟的影响。这种延迟会导致一种称为“网络异步”的现象，在这种情况下，设备发送的任何消息在实际到达其预期目的地时都会在一定程度上处于过时状态。因此，任何两个节点关于网络信息的本地视图始终是“不同步的”，关键挑战是每个单独的节点如何能够以最佳方式与其他节点通信和协作，尽管它们的本地视图是异步的。该项目研究网络异步下的最优网络协作策略，其结果可能导致迫切需要的下一代机器类型通信协议的高性能设计范例，从而显著提高自动车辆、传感器网络和许多其他物联网设备的通信效率。受最近发现的数据新鲜度控制的激励，该项目研究传感器和控制器以及整个网络如何在时间噪声的信息环路上进行最优协作，特别是如何在随机网络异步上执行(传输)定时优化。将对三个主要推力进行调查。在推力1中，将探索一个新的不动点方程框架，使现有的理论发展具体化，为优化调度表征和数值评估开辟新的场所。在推力2中，将开发新的分布式算法和数据新鲜度控制调度器，以最佳地适应任何未知的延迟分布。在推力3中，联合考虑以确认为中心、无确认和混合设计。并将研究量化传输层设计选择对数据新鲜度控制的影响。这些努力的结果将导致自主机器类型通信的新的理论特征、分布式算法和协议设计，其方式类似于互联网协议早期基于TCP的流量控制算法的开发。这一奖项反映了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。

A key force driving technology revolutions in the 21st century is the ever accelerating deployment of more powerful but physically smaller computing/sensing devices that are constantly and interactively connected through newer-generation wireless networks. There is interest in supporting device densities of up to one million devices per square kilometer, which, once achieved, would enable exponentially many innovations that further transform the landscape of modern society. A grand challenge of supporting this massive scale of machine-type communication is that modern wireless networks, while offering high throughput and broad coverage, are inevitably susceptible to random delay. This delay results in a phenomenon called "network asynchrony," for which any message sent by a device is always outdated to some random degree when it actually arrives at its intended destination. As such, the local views of any two nodes regarding network information are always "out-of-sync," and the key challenge is how each individual node can optimally communicate and collaborate with others despite their asynchronous local views. This project investigates the optimal network collaboration policies under network asynchrony, with results potentially leading to a high-performance design paradigm for the much-needed next-generation machine-type communication protocols, substantially improving the communication efficiency of autonomous vehicles, sensor networks, and many other Internet-of-Things devices.Motivated by the recent discovery of data freshness control, this projects studies how sensors and controllers, and the entire network in general, can optimally collaborate over a temporally noisy information loop, and particularly how to perform (transmission) timing optimization over random network asynchrony. Three major thrusts will be investigated. In thrust 1, a new fixed-point equation framework crystallizing the existing theoretic developments will be explored, opening up new venues for optimal scheduling characterization and numerical evaluation. In thrust 2, new distributed algorithms and data-freshness-control schedulers that optimally adapt to any unknown delay distribution will be developed. In Thrust 3, joint consideration of acknowledgement-centric, acknowledgement-free, and hybrid designs. and quantifying the impact of transport-layer design choices on data freshness control will be investigated. The results of these thrusts will lead to new theoretical characterizations, distributed algorithms, and protocol designs for autonomous machine-type communications in a way similar to the development of TCP-based flow-control algorithms in the early days of Internet protocols.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.