NeTS: Small: Lightweight, Accurate Network Estimation at the Wireless Edge

NeTS：小型：无线边缘的轻量级、准确的网络估计

• 批准号: 1718405
• 负责人: Aaron Striegel
• 金额: $ 50万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1718405&HistoricalAwards=false
• 关键词: NeTS; Small; Lightweight; Accurate; Network

Wireless technology has emerged as a critical piece of our modern, national economy. As more users, devices, and services lean heavily on a blend of WiFi and cellular service, it becomes important to understand whether our national wireless infrastructure will meet the demands of tomorrow. Unfortunately, the instruments for understanding such environments have lagged woefully behind and have not adapted to modern wireless technologies. The focus of this work is to bridge that gap to deliver significant improvements in handling WiFi and cellular. This research seeks to deliver instrumentation ten times faster than current technology while minimally draining the battery or impacting other users. The proposed work further explores whether one can achieve such instrumentation entirely for free, taking advantage of work the mobile device is already doing at present but simply ignoring. The research will create new software development kits to provide a ready-made wireless toolbox for app developers to cleverly improve the vast suite of apps available today.The proposed work seeks to explore the extent to which both modern WiFi and cellular links can be rapidly characterized, conducting both extensive lab experiments for validation as well as realizations of the software as additions to popular open source web serving and video streaming software. The proposed work centers on taking advantage of the intrinsic aggregation properties of most modern wireless systems. Through the clever use of sliced, structured, and reordered packet trains, the proposed work operates within existing TCP constructs to deliver accurate network characterization from 0-10 Mb/s in under 250 ms while requiring less than 100 KB of bandwidth. The net result is an characterization that presents that Available Bandwidth on the end-to-end path with minimal network and energy cost. In addition to the impacts of the software, multiple PhD graduate students will be trained, multiple REU (Research Experience for Undergraduate) students in under-represented groups will be mentored, and results will be disseminated through top tier publications. Final broader impacts include releasing extensive tutorials through an YouTube for the broader public on wireless issues.

无线技术已成为我们现代国民经济的关键部分。随着越来越多的用户，设备和服务在大大融合WiFi和蜂窝服务的融合中，了解我们国家无线基础设施是否满足明天的需求变得很重要。不幸的是，理解此类环境的工具已严重落后，没有适应现代无线技术。这项工作的重点是弥合这一差距，以在处理WiFi和细胞方面取得重大改进。这项研究旨在提供比当前技术快十倍的仪器，同时减少电池或影响其他用户的仪器。拟议的工作进一步探讨了人们是否可以免费实现此类仪器，利用移动设备目前已经在做的，而只是忽略了移动设备。这项研究将创建新的软件开发套件，为应用程序开发人员提供现成的无线工具箱，以巧妙地改善当今可用的大量应用程序。拟议的工作旨在探索现代WiFi和蜂窝链接可以快速表征的程度，从而进行验证的广泛实验实验，以验证广泛的软件以及对流行的开源网络启动的软件进行添加的软件，并实现了添加的软件。拟议的工作集中在利用大多数现代无线系统的固有聚合特性。通过巧妙地使用切片，结构化和重新排序的数据包列车，拟议的工作在现有的TCP构造中运行，以在250毫秒内提供准确的网络表征，同时需要小于100 kb的带宽。最终结果是一个表征，它显示了端到端路径上可用的带宽，其网络和能源成本最少。除了软件的影响外，还将对多个博士学位的研究生进行培训，将指导多个代表性小组中的多个REU（本科生的研究经验），并将通过顶级出版物来传播结果。最终的更广泛的影响包括通过YouTube发布广泛的教程，以在无线问题上为更广泛的公众发布。

项目成果

Sniffing Only Control Packets: A Lightweight Client-Side WiFi Traffic Characterization Solution

• DOI: 10.1109/jiot.2020.3041671
• 发表时间: 2021-04
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Lixing Song;A. Striegel;Alamin Mohammed

Swipe along: a measurement study of short video services

• DOI: 10.1145/3524273.3528186
• 发表时间: 2022-06
• 期刊: Proceedings of the 13th ACM Multimedia Systems Conference
• 作者: Shangyue Zhu;Theo Karagioules;Emir Halepovic;Alamin Mohammed;A. Striegel

CUP: Cellular Ultra-light Probe-based Available Bandwidth Estimation

CUP：基于蜂窝超轻探头的可用带宽估计

• DOI: 10.1109/iwqos52092.2021.9521270
• 发表时间: 2021
• 期刊: International Workshop on Quality of Service (IWQoS
• 作者: Song, Lixing;Halepovic, Emir;Mohammed, Alamin;Striegel, Aaron
• 通讯作者: Striegel, Aaron

A Lightweight Scheme for Rapid and Accurate WiFi Path Characterization

一种快速、准确的 WiFi 路径表征的轻量级方案

• DOI: 10.1109/icccn.2018.8487433
• 发表时间: 2018
• 期刊: Proc. of ICCCN
• 作者: Song, Lixing;Striegel, Aaron
• 通讯作者: Striegel, Aaron

A Frame-Aggregation-Based Approach for Link Congestion Prediction in WiFi Video Streaming

• DOI: 10.1109/icccn49398.2020.9209675
• 发表时间: 2020-08
• 期刊: 2020 29th International Conference on Computer Communications and Networks (ICCCN)
• 作者: Shangyue Zhu;Alamin Mohammed;A. Striegel