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.

这个项目的目标是设计和开发，第一次，一类新的基于序列的带宽比较和估计方法的网络环境与错误的接收端时间戳。所提出的工作从根本上不同于当前基于时间的带宽估计方法，因为该工作基于接收器处的分组序列信息（即，分组的到达顺序）而不是接收机处的分组时间信息（例如，每个数据包的确切到达时间）。此调查包括以下三个主要部分。1）相对带宽比较：设计并开发了一类基于序列的带宽比较方法，该方法相对比较多条路径的带宽信息，而不是精确估计每条路径的带宽信息。所提出的带宽比较方法不仅可以确定哪条路径更快，2）绝对带宽估计：设计并开发了一类基于序列的带宽估计方法，该方法仅利用分组序列信息就能准确估计出单个路径的带宽信息。3）多路径拥塞控制：设计和开发基于带宽比较的多径拥塞控制算法，以支持新兴的多径拥塞控制。预计在该项目中开发的带宽比较和估计方法不仅对网络研究人员有用，而且对云计算应用程序的大量用户也有用。为了实现更广泛的影响，研究者计划积极与开源云监控项目合作，并将开发的工具添加到他们的应用程序中，研究者将继续积极招募本科生，女性和少数民族学生参与研究项目，并致力于教学和课程开发。几个网络相关的课程和本科高级设计课程提供的部门将加强与最近的云网络主题和基于云的动手项目，从这个项目获得的研究成果将被纳入课程。

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