Collaborative Research: IMR: MM-1A: Scalable Statistical Methodology for Performance Monitoring, Anomaly Identification, and Mapping Network Accessibility from Active Measurements

合作研究:IMR:MM-1A:用于性能监控、异常识别和主动测量映射网络可访问性的可扩展统计方法

基本信息

  • 批准号:
    2319593
  • 负责人:
  • 金额:
    $ 20万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-10-01 至 2026-09-30
  • 项目状态:
    未结题

项目摘要

This collaborative project aims to develop and implement new statistical methodology for the detection and mapping of various aspects of delays and bandwidth quality in computer networks. Part I of the project will develop the so-called extreme delay tomography, where network links experiencing extreme delays or congestion will be identified. The goal is to do so by using only end-to-end measurements from the perimeter of the network without observing all links directly. Part II of the project will focus on combining multiple data sets and measurements to build a state-wide and potentially nation-wide map(s) of broadband accessibility at the resolution of a US-census block. The project brings together researchers from the University of Michigan, the University of California, Los Angeles, and Merit Network, with expertise in network tomography, statistics of extremes, and network measurement research. One core goal is to utilize and develop new theory on statistics of extremes that can be used to detect and identify anomalous delays in the network from end-to-end delay measurements. This will expand the fields of statistics, network tomography, and provide novel tools for situational awareness and quality of service. The second core activity of the project will contribute new statistical methodology for integrating multiple observational data sets with existing demographic covariates for the purpose of mapping broadband access. This research activity will contribute to the fields of data integration and transfer learning.The broader impacts of the project will be manifold. The direct impact of the research will be on: (i) Developing novel practical tools for network situational awareness and security; (ii) Mapping the broadband availability that will aid in understanding and identifying priority goals for public policy and also in addressing social disparities due to the broadband gap; (iii) The project will engage graduate and undergraduate students and thus contribute to training of the next generation of network measurement researchers and statisticians. The outcomes of the project will have a broader impact on the fields of statistics and network measurement research through novel theoretical, methodological, and algorithmic developments, data products and software. The latter will be disseminated to the broader research communities through journal publications, conference presentations and open-source software.An account of the research goals, achievements, and landmarks will be made publicly available on https://www.merit.edu/initiatives/#activeresearchprojects. This address will maintain pointers to data products, research reports, presentations, and events related to the sponsored research.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.
该合作项目旨在开发和实施新的统计方法,用于检测和绘制计算机网络中延迟和带宽质量的各个方面。 该项目的第一部分将开发所谓的极端延迟断层扫描,其中将识别经历极端延迟或拥塞的网络链路。其目标是通过仅使用来自网络周边的端到端测量来实现,而不直接观察所有链路。该项目的第二部分将侧重于结合多个数据集和测量,以建立一个全州和潜在的全国范围内的宽带接入地图在美国人口普查块的分辨率。该项目汇集了来自密歇根大学、加州大学、洛杉矶和Merit Network的研究人员,他们在网络断层扫描、极端统计和网络测量研究方面具有专长。 一个核心目标是利用和开发关于极端统计的新理论,该理论可用于从端到端延迟测量中检测和识别网络中的异常延迟。这将扩展统计、网络断层扫描等领域,并为态势感知和服务质量提供新的工具。该项目的第二项核心活动将有助于采用新的统计方法,将多个观测数据集与现有的人口协变量相结合,以绘制宽带接入地图。这项研究活动将有助于数据集成和迁移学习领域。该项目的广泛影响将是多方面的。研究的直接影响将是:㈠开发新的实用工具,以了解网络情况和保障网络安全; ㈡绘制宽带可用性图,这将有助于理解和确定公共政策的优先目标,并有助于解决宽带差距造成的社会差距; ㈢该项目将吸引研究生和本科生参与,从而有助于培训下一代网络计量研究人员和统计人员。该项目的成果将通过新的理论,方法和算法开发,数据产品和软件对统计和网络测量研究领域产生更广泛的影响。 后者将通过期刊出版物、会议介绍和开放源码软件向更广泛的研究界传播,研究目标、成就和里程碑的说明将在https://www.merit.edu/initiatives/#activeresearchprojects上公开。此地址将保留与赞助研究相关的数据产品、研究报告、演示文稿和活动的指针。此奖项反映了NSF的法定使命,并通过使用基金会的知识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

期刊论文数量(0)
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George Michailidis其他文献

Asymptotics for <math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si4.gif" display="inline" overflow="scroll" class="math"><mi>p</mi></math>-value based threshold estimation under repeated measurements
  • DOI:
    10.1016/j.jspi.2016.01.009
  • 发表时间:
    2016-07-01
  • 期刊:
  • 影响因子:
  • 作者:
    Atul Mallik;Bodhisattva Sen;Moulinath Banerjee;George Michailidis
  • 通讯作者:
    George Michailidis
Queueing Networks of Random Link Topology: Stationary Dynamics of Maximal Throughput Schedules
  • DOI:
    10.1007/s11134-005-0858-x
  • 发表时间:
    2005-05-01
  • 期刊:
  • 影响因子:
    0.700
  • 作者:
    Nicholas Bambos;George Michailidis
  • 通讯作者:
    George Michailidis
DNEA: an R package for fast and versatile data-driven network analysis of metabolomics data
  • DOI:
    10.1186/s12859-024-05994-1
  • 发表时间:
    2024-12-18
  • 期刊:
  • 影响因子:
    3.300
  • 作者:
    Christopher Patsalis;Gayatri Iyer;Marci Brandenburg;Alla Karnovsky;George Michailidis
  • 通讯作者:
    George Michailidis
Statistica Sinica Preprint No: SS-2022-0323
《统计》预印本编号:SS-2022-0323
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Abhishek Kaul;George Michailidis;Statistica Sinica
  • 通讯作者:
    Statistica Sinica
Preface: Computational biomedicine
  • DOI:
    10.1007/s10479-018-3116-4
  • 发表时间:
    2019-01-14
  • 期刊:
  • 影响因子:
    4.500
  • 作者:
    Anton Kocheturov;Panos Pardalos;George Michailidis
  • 通讯作者:
    George Michailidis

George Michailidis的其他文献

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{{ truncateString('George Michailidis', 18)}}的其他基金

ATD: Spatio-Temporal Modeling for Identifying Changes in Land Use
ATD:识别土地利用变化的时空模型
  • 批准号:
    2334735
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Change Point Detection for Data with Network Structure
网络结构数据变点检测
  • 批准号:
    2348640
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Geospatial Modeling and Risk Mitigation for Human Movement Dynamics under Hurricane Threats
合作研究:ATD:飓风威胁下人类运动动力学的地理空间建​​模和风险缓解
  • 批准号:
    2319552
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Change Point Detection for Data with Network Structure
网络结构数据变点检测
  • 批准号:
    2210358
  • 财政年份:
    2022
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
ATD: Spatio-Temporal Modeling for Identifying Changes in Land Use
ATD:识别土地利用变化的时空模型
  • 批准号:
    2124507
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
CDS&E: Statistical Methodology for Analysis and Forecasting with Large Scale Temporal Data
CDS
  • 批准号:
    1821220
  • 财政年份:
    2018
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
ATD: Collaborative Research: Extremal Dependence and Change-Point Detection Methods for High-Dimensional Data Streams with Applications to Network Cybersecurity
ATD:协作研究:高维数据流的极端依赖性和变点检测方法及其在网络网络安全中的应用
  • 批准号:
    1830175
  • 财政年份:
    2018
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
BIGDATA: Collaborative Research: IA: F: Too Interconnected to Fail? Network Analytics on Complex Economic Data Streams for Monitoring Financial Stability
BIGDATA:协作研究:IA:F:互联性太强以至于不会失败?
  • 批准号:
    1632730
  • 财政年份:
    2016
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
CyberSEES: Type 2: Collaborative Research: Tenable Power Distribution Networks
Cyber​​SEES:类型 2:协作研究:可维持的配电网络
  • 批准号:
    1540093
  • 财政年份:
    2015
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: Statistical Methodology for Network based Integrative Analysis of Omics Data
合作研究:基于网络的组学数据综合分析统计方法
  • 批准号:
    1545277
  • 财政年份:
    2015
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant

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相似海外基金

Collaborative Research: IMR: MM-1C: Methods for Active Measurement of the Domain Name System
合作研究:IMR:MM-1C:域名系统主动测量方法
  • 批准号:
    2319367
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IMR: MM-1B: Privacy-Preserving Data Sharing for Mobile Internet Measurement and Traffic Analytics
合作研究:IMR:MM-1B:移动互联网测量和流量分析的隐私保护数据共享
  • 批准号:
    2319486
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IMR: MM-1A: Scalable Statistical Methodology for Performance Monitoring, Anomaly Identification, and Mapping Network Accessibility from Active Measurements
合作研究:IMR:MM-1A:用于性能监控、异常识别和主动测量映射网络可访问性的可扩展统计方法
  • 批准号:
    2319592
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IMR: MM-1B: Privacy-Preserving Data Sharing for Mobile Internet Measurement and Traffic Analytics
合作研究:IMR:MM-1B:移动互联网测量和流量分析的隐私保护数据共享
  • 批准号:
    2344341
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    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IMR: MM-1B: Automating Privacy-Preserving Data Sharing of Campus Network Traffic Logs
合作研究:IMR:MM-1B:自动化校园网络流量日志的隐私保护数据共享
  • 批准号:
    2319421
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IMR: MM-1B: Privacy-Preserving Data Sharing for Mobile Internet Measurement and Traffic Analytics
合作研究:IMR:MM-1B:移动互联网测量和流量分析的隐私保护数据共享
  • 批准号:
    2319488
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
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Collaborative Research: IMR: MM-1A: Functional Data Analysis-aided Learning Methods for Robust Wireless Measurements
合作研究:IMR:MM-1A:用于稳健无线测量的功能数据分析辅助学习方法
  • 批准号:
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  • 资助金额:
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