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

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。高速传输数据的瓶颈往往是终端系统的性能。在没有关于接收端系统的工作负载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。这通常会导致极端和性能差之间的振荡。为了优化传输协议的性能，实现重要的流量控制功能，重要的是估计接收端系统的有效瓶颈率。在这个项目中，我们将使用建模和终端系统的主动分析来估计这一速率。 我们将开发用于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的嵌入式网络模型。我们将开发一个软件工具，与现有的传输协议相结合。我们将针对具有不同配置和工作负载的不同类型的端系统进行实验分析。我们将应用和扩展已经提出的方法，以解决突发性工作负载和相关的服务时间的计算机系统的性能分析的网络模型的局限性。 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，培养研究生和本科生的分析和实验方法，并开发有关下一代计算机系统和分布式应用程序的知识和直觉。

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.