CSR:Small:Estimating the End-system Network I/O Bottleneck Rate to Optimize Transport Layer Performance

CSR：小：估计终端系统网络 I/O 瓶颈率以优化传输层性能

• 批准号: 0917315
• 负责人: Dipak Ghosal
• 金额: $ 41.09万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0917315&HistoricalAwards=false
• 关键词: CSR; Small; Estimating; End; system

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The bottleneck for the transferring data at very high speeds often turns out to be the end-system performance. In the absence of definitive knowledge about the workload at the receiving end-system, the sender's transmission rate often overshoots the critical bottleneck rate of the receiver. This typically results in oscillations between the extremes and poor performance. To optimize the performance of the transport protocols and achieve the important flow control functionality, it is important to estimate the receiving end-system effective bottleneck rate. In this project we will use modeling and active analysis of the end-system to estimate this rate. We will develop queueing network models for representing the different multicore and multiprocessor end-systems running different types of workloads. We will develop a software tool to be integrated with existing transport protocols. We will carry out experimental analysis for different types of end-systems with different configurations and workloads. We will apply and extend methods that have been proposed to address the limitations of queueing network models for performance analysis of computer systems with bursty workloads and correlated service times. The software tool will be made available to the research community to analyze and optimize distributed applications and systems. The research project will provide a framework to train graduate and undergraduate students in both analytical and experimental methods, and develop knowledge and intuition about next generation computer systems and distributed applications.

该奖项是根据2009年《美国复苏和再投资法案》(公法111-5)提供资金的。以非常高的速度传输数据的瓶颈往往是终端系统性能。在缺乏关于接收端系统的工作负荷的明确知识的情况下，发送方的传输速率常常超过接收方的临界瓶颈速率。这通常会导致两极之间的振荡和较差的性能。为了优化传输协议的性能，实现重要的流量控制功能，估计接收端系统的有效瓶颈率是很重要的。在本项目中，我们将使用终端系统的建模和主动分析来估计这一比率。我们将开发排队网络模型，以表示运行不同类型工作负载的不同多核和多处理器终端系统。我们将开发一个与现有传输协议集成的软件工具。我们将对不同类型、不同配置和不同工作负载的终端系统进行实验分析。我们将应用和扩展已提出的方法，以解决排队网络模型在具有突发工作负载和相关服务时间的计算机系统的性能分析中的局限性。该软件工具将提供给研究界，以分析和优化分布式应用程序和系统。该研究项目将提供一个框架，以培训研究生和本科生在分析和实验方法方面，并发展关于下一代计算机系统和分布式应用的知识和直觉。