NSF-BSF: CNS Core: Small: Improving Wireless Networks Robustness via Weather-Sensitive Predictive Management

NSF-BSF：CNS 核心：小型：通过天气敏感预测管理提高无线网络的稳健性

• 批准号: 1910757
• 负责人: Gil Zussman
• 金额: $ 40万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910757&HistoricalAwards=false
• 关键词: NSF; BSF; CNS; Core; Small

This project focuses on the wireless networks that are used in the backbone of cellular, smart cities, and emerging 5G networks. These networks rely on millimeter-wave (mmWave) frequencies, which are sensitive to weather conditions and specifically to rain events. Improving resilience to such events, the rapid increase in wireless traffic, and the Quality of Service (QoS) demands of mission-critical smart city applications, all call for dynamic network management schemes. Therefore, weather-sensitive network control and management approaches will be developed, aiming to improve network resilience and performance. The innovation of this project is to use weather-affected measurements of wireless link states in the network to accurately predict their future states and to provide input to network control schemes. These schemes include adjustments of links' modes and network topology to the moving rain, prior to its effects on the signals. The algorithms designed will build on extensive datasets of wireless links and the algorithms will be evaluated and demonstrated in the National Science Foundation-funded COSMOS platform for advanced wireless research (PAWR) testbed. The project will have a strong outreach component, including programs for Harlem public school teachers and Israeli K-12 students. On a societal scale, the development of algorithms that enhance network resilience in face of weather events can improve network connectivity in cases where it is most needed (e.g., emergency situations). In general, enhancing the performance of future smart city and 5G networks will help bridge the digital divide and bringing better connectivity to under-served communities.Specifically, the project focuses on backhaul and fronthaul networks which are currently transitioning to E-band (60-90 gigahertz) links that are very sensitive to rain events. Contrary to legacy (4G) cellular networks where local physical layer adaptation has been sufficient, in emerging smart city and 5G networks (that will require low latency and high bandwidth), link and network layer adaptations will be essential. Algorithms that use the self-extracted attenuation measurements from the network to predict the channel states throughout the network will be developed based on relationships between weather and signal attenuation. Then, weather-sensitive cross-layered control algorithms will be developed. These algorithms will jointly optimize power, modulation and coding, channel allocation, and routing to satisfy QoS requirements in response to predicted changes in network conditions. Finally, the project's contributions will include analysis of first-of-their-kind mmWave backhaul measurements from a smart city network in Israel and unique evaluation in a city-scale test-bed that integrates first-of-their-kind mmWave transceivers.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.

该项目重点关注蜂窝、智能城市和新兴 5G 网络骨干中使用的无线网络。这些网络依赖于毫米波 (mmWave) 频率，毫米波频率对天气条件特别是降雨事件很敏感。提高对此类事件的恢复能力、无线流量的快速增长以及关键任务智能城市应用的服务质量 (QoS) 要求，都需要动态网络管理方案。因此，将开发对天气敏感的网络控制和管理方法，旨在提高网络的弹性和性能。该项目的创新之处在于利用受天气影响的网络中无线链路状态测量来准确预测其未来状态，并为网络控制方案提供输入。这些方案包括在雨对信号产生影响之前对链路模式和网络拓扑进行调整。设计的算法将建立在广泛的无线链路数据集的基础上，并且这些算法将在美国国家科学基金会资助的高级无线研究 COSMOS 平台 (PAWR) 测试台中进行评估和演示。该项目将有一个强大的外展部分，包括针对哈莱姆区公立学校教师和以色列 K-12 学生的项目。在社会层面上，开发增强网络应对天气事件弹性的算法可以在最需要的情况下（例如紧急情况）改善网络连接。总体而言，增强未来智慧城市和 5G 网络的性能将有助于弥合数字鸿沟，并为服务不足的社区带来更好的连接。具体而言，该项目重点关注目前正在向 E 频段（60- 90 GHz）对降雨事件非常敏感的链路。与本地物理层适配已足够的传统 (4G) 蜂窝网络相反，在新兴智慧城市和 5G 网络（需要低延迟和高带宽）中，链路和网络层适配将至关重要。将根据天气和信号衰减之间的关系开发使用从网络中自提取的衰减测量来预测整个网络的信道状态的算法。然后，将开发天气敏感的跨层控制算法。这些算法将联合优化功率、调制和编码、信道分配和路由，以满足 QoS 要求，响应网络条件的预测变化。最后，该项目的贡献将包括对以色列智能城市网络的首创毫米波回程测量进行分析，以及在集成首创毫米波收发器的城市规模测试台中进行独特评估。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

项目成果

Switching in the Rain: Predictive Wireless x-haul Network Reconfiguration

• DOI: 10.1145/3570616
• 发表时间: 2022-03
• 期刊: Proceedings of the ACM on Measurement and Analysis of Computing Systems
• 作者: I. Kadota;Dror Jacoby;H. Messer;G. Zussman;J. Ostrometzky

Real-Time Video Anonymization in Smart City Intersections

• DOI: 10.1109/mass56207.2022.00078
• 发表时间: 2022-10
• 期刊: 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
• 作者: Alex Angus;Zhuoxu Duan;G. Zussman;Z. Kostić

Short-Term Prediction of the Attenuation in a Commercial Microwave Link Using LSTM-based RNN

使用基于 LSTM 的 RNN 对商用微波链路中的衰减进行短期预测

• DOI: 10.23919/eusipco47968.2020.9287835
• 发表时间: 2021
• 期刊: 2020 28th European Signal Processing Conference (EUSIPCO
• 作者: Jacoby, Dror;Ostrometzky, Jonatan;Messer, Hagit
• 通讯作者: Messer, Hagit

Adaptive Fuzzy-Based Models for Attenuation Time Series Forecasting

用于衰减时间序列预测的自适应模糊模型

• 发表时间: 2022
• 期刊: 2021
• 作者: D. Jacoby, J. Ostrometzky

COSMOS educational toolkit: using experimental wireless networking to enhance middle/high school STEM education

COSMOS 教育工具包：使用实验性无线网络增强初中/高中 STEM 教育

• DOI: 10.1145/3431832.3431839
• 发表时间: 2020
• 期刊: ACM SIGCOMM Computer Communication Review
• 影响因子: 2.8
• 作者: Skrimponis, Panagiotis;Makris, Nikos;Rajguru, Sheila Borges;Cheng, Karen;Ostrometzky, Jonatan;Ford, Emily;Kostic, Zoran;Zussman, Gil;Korakis, Thanasis
• 通讯作者: Korakis, Thanasis