NeTS: Small: Exploring the Design Space of Bandwidth Estimation Methods Using Packet Sequence Information

NeTS：小：探索使用数据包序列信息的带宽估计方法的设计空间

• 批准号: 1616087
• 负责人: Lisong Xu
• 金额: $ 49.89万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1616087&HistoricalAwards=false
• 关键词: NeTS; Small; Exploring; Design; Space

The goal of this project is to design and develop, for the first time, a novel class of sequence-based bandwidth comparison and estimation methods for network environments with faulty receiver-side timestamping. The proposed work is fundamentally different from the current time-based bandwidth estimation methods, because this work is based on the packet sequence information at a receiver (i.e., the arriving order of packets) instead of the packet time information at the receiver (e.g., the exact arrival time of each packet).This investigation consists of the following three major components.1) Relative Bandwidth Comparison: Design and develop a class of sequence-based bandwidth comparison methods, which relatively compare the bandwidth information of multiple paths instead of accurately estimating the bandwidth information of each individual path. The proposed bandwidth comparison methods can determine not only which path is faster but also how much faster using only the packet sequence information.2) Absolute Bandwidth Estimation: Design and develop a class of sequence-based bandwidth estimation methods, which can accurately estimate the bandwidth information of an individual path using only the packet sequence information.3) Multi-Path Congestion Control: Design and develop bandwidth comparison based multi-path congestion control algorithms to support emerging multi-homed hosts.It is expected that the bandwidth comparison and estimation methods to be developed in this project will be useful not only for networking researchers but also for the large number of users of cloud computing applications. To achieve an even broader impact, the investigator plans to actively work with open source cloud monitoring projects and add the developed tools into their applications.The investigator will continue to actively recruit undergraduate, female, and minority students into the research projects, and to be committed to teaching and curriculum development. Several networking related courses and the undergraduate senior design course offered in the department will be enhanced with more recent cloud network topics and cloud-based hand-on projects, and research results obtained from this project will be incorporated into the courses.

该项目的目的是首次设计和开发基于序列的带宽比较和估计方法，该方法的接收器端时间戳有故障。所提出的工作与当前基于时间的带宽估计方法根本不同，因为这项工作基于接收器的数据包序列信息（即数据包到达顺序），而不是接收器处的数据包时间信息，例如，每个数据包的精确到达时间（每个数据表的精确到达时间）。此临界序列由以下三个序列组成。11相对阶段。比较方法，该方法相对比较了多个路径的带宽信息，而不是准确估计每个单个路径的带宽信息。所提出的带宽比较方法不仅可以确定哪种路径更快，而且仅使用数据包序列信息更快地确定了多少速度。2）绝对带有估计的估计：设计和开发一类基于序列的带宽估计方法，可以准确地估算单个路径的带宽信息，仅使用数据包序列信息进行组合。支持新兴的多主主机的算法。期望在本项目中开发带宽比较和估计方法，不仅对网络研究人员，而且对云计算应用程序的大量用户都有用。为了实现更广泛的影响，研究者计划积极地与开源云监控项目合作，并将开发的工具添加到其应用程序中。研究人员将继续积极招募本科生，女性和少数族裔学生进入研究项目，并致力于教学和课程发展。通过最近的云网络主题和基于云的手工项目，将增强与该项目相关的几个与网络相关的课程以及本科部门提供的本科高级设计课程，从该项目获得的研究结果将纳入课程中。

项目成果

Evaluation of the ProgHW/SW Architectural Design Space of Bandwidth Estimation

带宽估计的ProgHW/SW架构设计空间评估

• 发表时间: 2023
• 期刊: Proceedings of Passive and Active Measurement
• 作者: Fang, Tianqi;Xu, Lisong;Srisa-an, Witawas;Patel, Jay
• 通讯作者: Patel, Jay