CNS Core: Small: Significantly Improving Networked Applications using Congestion-Aware Transport Modeling

Web和视频等互联网应用程序的性能在很大程度上取决于底层网络条件。尽管网络技术取得了一些进步，但互联网应用程序的性能问题并没有得到完全缓解。这是因为，考虑到网络的可变性和应用工作负载，没有一种协议或参数设置在任何时候都能工作得最好。该项目的目标是开发一个新的、统一的、实用的建模框架，能够准确地预测不同网络条件和参数下的应用性能，首先开发一个新的拥塞感知传输控制协议性能模型，然后将该模型扩展到应用层，从而实现其预定的目标。在TCP层，性能将通过分析建模，但将通过经验观察到的网络拥塞和传输速率之间的关系来增强性能。该模型将使用预测和聚类技术基于来自目标流附近的现有流或历史流的网络信息来引导模型参数。对于网络，该模型将被扩展到预测页面加载时间，而对于视频应用，将使用TCP吞吐量预测来驱动码率选择算法。由于视频和网络流量几乎占据了互联网上的所有流量，因此本研究针对的是广泛的人群。这项工作为初创公司和较小的公司提供了系统地了解不同协议对提高性能的影响的方法，从而对初创公司和较小的公司有利。作为正在进行的合作的一部分，该项目的成果将用于改善发展中地区的网络性能。PIS将向本科生和高中生介绍基于Web和视频性能、网络协议建模和测量研究的项目。在吸引高中生和本科生参与他们的研究方面，PI有着成功的记录。作为该项目的一部分而设计的软件将在公共网站http://www.cs.stonybrook.edu/~arunab/econ.上发布电子数据将在内部存档。所有数据将在发布后保留至少5年；根据其规模和外部兴趣，可能会更长时间。该奖项反映了NSF的法定使命，并已被认为值得支持，通过使用基金会的智力价值和更广泛的影响审查标准进行评估。

The performance of Internet applications such as Web and Video depends critically on the underlying network conditions. Despite several advances in networking technology, the performance problems of Internet applications have not been fully alleviated. This is because, given the variability in the network and the application workload, no one protocol or parameter setting works best at all times. The goal of this project is to develop a novel, unified, and practical modeling framework that can accurately predict the performance of applications under different network conditions and parameters.The project will achieve its stated goals by first developing a new congestion-aware TCP (Transmission Control Protocol) performance model, and then extending this model to encompass the application layer. At the TCP layer, performance will be modeled analytically, but will be augmented by empirically observed relationship between congestion in the network and the delivery rate. The model will use predictive and clustering techniques bootstrap model parameters based on network information from existing or historical flows in the vicinity of the target flow. For Web, this TCP model will be extended to predict page load times while for video applications, TCP throughput predictions will be used to drive the bitrate selection algorithm.This research targets a broad segment of the population since video and web traffic makes up almost all of the traffic on the Internet. This work is beneficial to startups and smaller companies by providing means to systematically understand the effect of different protocols to improve performance. The results of this project will be used to improve the Web performance in developing regions as part of an ongoing collaboration. The PIs will introduce projects based on Web and Video performance, network protocol modeling, and measurement studies to undergraduate and high school students. The PIs have a successful track record of engaging high-school students and undergraduates in their research.The software designed as part of this project will be released on a public site http://www.cs.stonybrook.edu/~arunab/econ. Electronic data will be archived internally. All data will be kept for at least 5 years after publication; likely longer, depending on its size and outside interest.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.