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

CIF：小：随机网络异步的时序优化 - 理论和分布式算法

基本信息

批准号：
2008527
负责人：
Chih-Chun Wang
金额：
$ 16.5万
依托单位：
Purdue University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2023-01-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008527&HistoricalAwards=false
关键词：
CIF Small Timing Optimization Over

项目摘要

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 This delay results in a phenomenon called "network asynchrony," for which any message sent by a device is always outdated to some random degree when it actually arrives at its intended destination.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.

推动 21 世纪技术革命的关键力量是不断加速部署功能更强大但体积更小的计算/传感设备，这些设备通过新一代无线网络持续交互连接。人们有兴趣支持每平方公里高达一百万台的设备密度，一旦实现，将带来指数级的许多创新，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巨大挑战是，现代无线网络虽然提供高吞吐量和广泛的覆盖范围，但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，即设备发送的任何消息在实际到达其预期目的地时总是会在某种程度上随机地过时。因此，任何两个节点关于网络信息的本地视图总是“不同步”，关键的挑战是每个单独的节点如何能够在本地视图异步的情况下与其他节点进行最佳通信和协作。该项目研究网络异步下的最佳网络协作策略，其结果可能为急需的下一代机器类型通信协议带来高性能设计范式，从而大幅提高自动驾驶车辆、传感器网络和网络的通信效率。许多其他物联网设备。受最近发现的数据新鲜度控制的推动，该项目研究传感器和控制器以及整个网络如何在暂时嘈杂的信息循环中进行最佳协作，特别是如何执行（传播）随机网络异步的时序优化。将调查三个主要重点。在主旨 1 中，将探索一个新的定点方程框架，该框架具体化了现有的理论发展，为最优调度表征和数值评估开辟了新的场所。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程序，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。这些推动力的成果将带来新的理论特征、分布式算法和自主机器类型通信的协议设计，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。该奖项反映了通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。