NeTS: Small: Collaborative Research: A Fast and Flexible Transport Architecture for High Speed Networks

现代数据中心网络和私有广域网是云计算的基础。如今，由于缺乏灵活性，运营商最终会过度供应网络，以避免性能瓶颈。该项目将使这些网络更高效，更能适应应用程序的需求。具体来说，本研究探讨了加权传输抽象作为优化网络带宽分配的系统的灵活和健壮的基础。该研究回顾了该领域的经典理论框架——网络效用最大化（NUM），并为NUM开发了一种新颖实用的分布式算法，该算法比以前的方法快得多，因此适用于现代高速网络，如数据中心结构。该项目旨在设计和建造一个灵活的交通体系结构。所建议的体系结构有两个主要的技术组件：1。加权传输：本研究开发了一种基于权重的传输，而不是使用流量来控制带宽分配。为了调整带宽分配，流在其包头中调整权重字段；然后，每个链路将其带宽按权重的比例分配给竞争流。2. 快速效用最大化：该项目利用加权传输来设计一个网络结构，该网络结构可以针对不同的带宽分配目标进行动态调整，例如最小化流/共流完成时间或服务水平公平性。ppi计划与能够影响标准的公司密切互动，并利用提议的想法建立商业系统。该教育计划包括将该研究成果纳入本科和研究生课程，并提供了一个机会，采用“自上而下”的方法来教授交通体系结构，重点关注关键带宽分配目标以及它们如何影响实际应用。课程材料将通过麻省理工学院开放课程和麻省理工学院MOOC广泛提供。

Modern datacenter networks and private wide area networks underpin cloud computing. Today, due to the lack of flexibility, operators end up over provisioning their networks significantly to avoid performance bottlenecks. This project will make these networks more efficient and more tuned to the application's needs. Specifically, this investigation explores a weighted transport abstraction as a flexible and robust substrate for systems that optimize a network's bandwidth allocation. The proposed research revisits a classic theoretical framework in this space, Network Utility Maximization (NUM), and develops a novel and practical distributed algorithm for NUM that is significantly faster than prior approaches, and is thus applicable to modern high speed networks such as datacenter fabrics. This project seeks to design and build a flexible transport architecture. The proposed architecture has two main technical components: 1. Weighted Transport: Instead of using flow rates to control the bandwidth allocation, this research develops a transport based on weights. To tune the bandwidth allocation, flows adapt a weight field in their packet headers; each link then divides its bandwidth among contending flows in proportion to their weights. 2. Fast Utility Maximization: This project leverages the weighted transport to design a network fabric that can be dynamically tuned for different bandwidth allocation objectives such as minimizing flow/coflow completion time, or service-level fairness. The PIs plan to interact closely with companies that can influence standards and build commercial systems using the proposed ideas. The education plan includes the incorporation of this research's findings into the undergraduate and graduate curricula and offers an opportunity to take a "top-down" approach to teaching transport architectures with a focus on key bandwidth allocation objectives and how they affect real applications. The course material will be made widely available through MIT OpenCourseWare and on the MITx MOOC.