IMR: MM-1A: ADDRESS: Augment, Denoise and Debias cRowdsourced mEasurements for Statistical Synthesis of internet access characterization

IMR：MM-1A：地址：互联网接入特征统计综合的增强、降噪和去偏众包测量

• 批准号: 2220417
• 负责人: Elizabeth Belding
• 金额: $ 60万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2220417&HistoricalAwards=false
• 关键词: IMR; MM; 1A; ADDRESS; Augment

The U.S. suffers from digital inequality that stretches in multiple dimensions. Several demographic and socioeconomic factors, such as race, ethnicity, and income, as well as population density, are often indicators of Internet availability and quality. To fully bridge the Internet access divide and best allocate available funding, policymakers need to understand the state of Internet accessibility and quality at fine-grained geographical granularity. The goal of this project is to make the best use of crowdsourced Internet measurement data to estimate the distribution of fixed Internet quality at different levels of geospatial granularity with as high accuracy as possible.To do so, the projects plans to make the following contributions: (i) to develop a Broadband Offerings Tool that aggregates ISP broadband plan offerings and links that data with crowdsourced measurements and socioeconomic data to predict user subscription plans, (ii) to develop new methodologies and algorithms that can detect noisy data points, such as speed test measurements that report bottlenecks in WiFi access or remote peering links, which bias the understanding of Internet quality, (iii) to propose new statistical techniques that use the resulting dataset to output a debiased dataset that removes the spatial, temporal, and demographic biases inherent in crowdsourced Internet measurement data.Digital inequality continues to persist in the U.S., deepened by the work-from-home and remote schooling resulting from the COVID-19 pandemic. The outputs of this work will be used to report the distribution of Internet quality in a region and predict that of regions for which less data is available. This work will also reveal demographic variables that most influence the U.S. digital divide. The outcomes of this project can be used to inform local, state and federal governments about where investments must be made to ensure all Americans have access to high quality Internet.A project website will be established, which will contain information about research methodology, models and outcomes. The likely URL is broadband.cs.ucsb.edu. The website will be maintained for the duration of the project, and at least a year thereafter.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.

美国的数字不平等遭受了多个维度。种族，种族和收入等几个人口和社会经济因素以及人口密度通常是互联网可用性和质量的指标。为了完全弥合互联网访问鸿沟，最佳分配可用的资金，决策者需要在细粒度的地理粒度下了解Internet可访问性和质量的状态。 The goal of this project is to make the best use of crowdsourced Internet measurement data to estimate the distribution of fixed Internet quality at different levels of geospatial granularity with as high accuracy as possible.To do so, the projects plans to make the following contributions: (i) to develop a Broadband Offerings Tool that aggregates ISP broadband plan offerings and links that data with crowdsourced measurements and socioeconomic data to predict user subscription plans, (ii) to develop new methodologies and algorithms that can detect noisy data points, such as speed test measurements that report bottlenecks in WiFi access or remote peering links, which bias the understanding of Internet quality, (iii) to propose new statistical techniques that use the resulting dataset to output a debiased dataset that removes the spatial, temporal, and demographic biases inherent in crowdsourced Internet measurement Data.Digital不平等在美国继续持续存在，这是由于COVID-19-19所产生的工作和偏远的教育加深了。这项工作的输出将用于报告一个区域中互联网质量的分布，并预测可用数据较少的区域的分布。这项工作还将揭示人口变量，最大程度地影响美国数字鸿沟。该项目的结果可用于向当地，州和联邦政府告知必须在何处进行投资以确保所有美国人都可以访问高质量的互联网。将建立一个项目网站，其中包含有关研究方法论，模型和结果的信息。可能的URL是宽带。cs.ucsb.edu。该网站将在该项目的期限内维持，此后至少一年。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来获得支持。

项目成果

Decoding the Divide: Analyzing Disparities in Broadband Plans Offered by Major US ISPs

解码鸿沟：分析美国主要 ISP 提供的宽带计划的差异

• DOI: 10.1145/3603269.3604831
• 发表时间: 2023
• 期刊: ACM Sigcomm
• 作者: Paul, Udit;Gunasekaran, Vinothini;Liu, Jiamo;Narechania, Tejas N.;Gupta, Arpit;Belding, Elizabeth
• 通讯作者: Belding, Elizabeth

The importance of contextualization of crowdsourced active speed test measurements

• DOI: 10.1145/3517745.3561441
• 发表时间: 2022-10
• 期刊: Proceedings of the 22nd ACM Internet Measurement Conference
• 作者: Udit Paul;Jiamo Liu;Mengyang Gu;Arpit Gupta;E. Belding-Royer