NeTS: Small: Towards Exposing and Mitigating End-to-End TCP Performance and Fairness Issues in Data Center Networks

虽然TCP被设计成可以在任何环境中工作，但每当将它引入没有明确设计和测试的新环境（例如无线网络、卫星网络、大容量网络）时，它就会出现很长时间的问题。对TCP构成挑战的一个类似的新领域是最近流行起来的数据中心和云环境。该项目将研究TCP在现代云计算和数据中心环境中面临的端到端挑战，并提出解决这些挑战的解决方案。具体来说，它主要关注数据中心和云环境中围绕TCP的三个主要问题：首先，在虚拟化云环境中，当多个虚拟机共享CPU时，每个虚拟机的CPU访问延迟（即虚拟机等待CPU的时间间隔）在数十/数百毫秒的数量级上，可能比典型的亚毫秒级网络rtt高几个数量级。这种高RTT导致TCP吞吐量显著降低。其次，在多根数据中心网络中，在某些条件下，共享公共链路的TCP连接表现出严重的不公平。最后，在当今的数据中心网络中，等成本多路径路由（ECMP）通常用于跨多个路径分割流量，但它可能会导致严重的负载不平衡。研究人员过去一直不建议使用包级多路径路由，因为它可能会导致重新排序，从而降低TCP吞吐量。然而，目前尚不清楚这种与多路径路由的不良交互是否存在于对称拓扑（如胖树）或更普遍的多根树拓扑下。智力价值：该项目的目标是全面研究上述三个主要问题，提出新的解决方案来解决问题，最后，通过实际原型实现和广泛的评估来验证这些解决方案和假设。(1)为了解决TCP在虚拟化云环境中的性能恶化问题，该项目将探索一种称为传输功能委托的新方法，其中某些TCP功能被委托给驱动程序域或管理程序。(2)它将使用真实的测试平台进行广泛的实验，以暴露和表征不公平问题，并提出和评估经典解决方案（例如，RED）和一种称为等长度路由的新路由算法来缓解这一问题。(3)在具有多根树等规则拓扑结构的数据中心网络环境中，它将重新审视细粒度多路径流量分割协议与TCP交互不良的传统观点。更广泛的影响：本研究的更广泛的影响包括以下方面：(1)它将有助于改善TCP的关键方面，如数据中心和云环境中的性能和公平性，这将使所有数据中心系统和应用受益。(2)本研究成果将向产业转化。(3)本研究成果将整合到操作系统、计算机网络、云计算等课程中。它还将为研究生提供培训，预计将有几篇博士论文出自这项研究。(4)它将包括少数民族（代表性不足的少数民族和妇女）的参与。

While TCP was designed to work in any environment, it has a long history of problems whenever introduced in newer environments (e.g., wireless networks, satellite networks, high-capacity networks) that it was not explicitly designed and tested for. A similar new frontier that challenges TCP is the data center and cloud environments that have become popular in recent times. This project will conduct research on exposing end-to-end challenges that TCP faces in the modern cloud computing and data center environments and propose solutions to address them. Specifically, it focuses on three major issues surrounding TCP in data center and cloud environments: First, in virtualized cloud environments, when multiple VMs share the CPU, CPU access latency for each VM (i.e., the interval during which a VM waits for the CPU) is in the order of tens/hundreds of milliseconds and can be orders of magnitude higher than the typical sub-millisecond network RTTs. This high RTT causes significant reduction in TCP throughput. Second, in multirooted data center networks, under certain conditions, TCP connections sharing a common link exhibit severe unfairness. Finally, in data center networks today, equal-cost multipath routing (ECMP) is often used to split traffic across multiple paths, but it can potentially cause significant load imbalance. Researchers have refrained from suggesting packet-level multipath routing in the past because of its ability to cause reordering that may reduce TCP throughput. It is however not clear whether this poor interactions with multipath routing exists even under symmetric topologies such as fattrees, or more generally, multi-rooted tree topologies. Intellectual Merit: The goal of this project is to comprehensively investigate these afore-mentioned three major issues discussed above, propose new solutions to address the problems, and finally, validate these solutions and hypotheses using real prototype implementations and through extensive evaluations. (1) To address TCP's performance deterioration in virtualized cloud environments, the project will explore a new approach called transport function delegation, where certain TCP functions are delegated to the driver domain or hypervisor. (2) It will conduct extensive experimentation using real testbeds to expose, and characterize the unfairness issue, and also propose and evaluate classic solutions (e.g., RED) and a new routing algorithm called equal-length routing to mitigate this problem. (3) It will revisit the conventional wisdom that fine-grained multi-path traffic splitting protocols interact poorly with TCP, in the context of data center networks which have regular topologies such as multi-rooted trees. Broader Impact: The broader impact of this research comprises of the following: (1) It will help improve the key aspects of TCP such as performance and fairness in data center and cloud environments, that will benefit all data center systems and applications. (2) Results of this research will be transferred to industry. (3) Results of this research will be integrated into courses such as operating systems, computer networks, and cloud computing. It will also provide training to graduate students and several Ph.D. theses are expected to come out of this research. (4) It will include participation of minorities (under-represented minorities and women).