NeTS: Small: Collaborative Research: Software Defined Network Function Virtualization (SDNFV) - Flexible, High Performance Network and Data Center Virtualization

传统的计算机网络是由硬件设备（如路由器、防火墙和交换机）构建的，以实现功能。这些设备可以高速处理网络数据包，但灵活性很小，因为它们是基于专用硬件的。最近在多核处理器和高速网络接口卡方面的改进已经启用了网络功能虚拟化（NFV），它允许这些网络组件在商用计算服务器上运行。NFV使网络数据处理元素像软件一样运行，允许它们动态部署，或者随着网络工作负载的变化轻松修改和调优。与此同时，软件定义网络（SDN）作为一种通过集中控制平面功能更容易地管理网络服务的方式越来越受欢迎。本研究探讨了NFV和SDN的融合如何为互联网服务提供商（isp）的客户提供一种新型的高度动态的网络服务，并赋予云计算客户对数据中心资源的更大控制权。这项工作将探索支持网络组件在虚拟机内以超过10gbps的速度运行所需的软件机制，以及协调这些组件的高性能和低成本所需的算法和控制体系结构。该项目针对软件定义网络功能虚拟化（SDNFV）的两个应用领域。第一种是针对网络提供商的动态服务，主要研究人员（pi）正在开发SDNFV平台，通过利用网络接口控制器（NIC）轮询和共享内存进行零复制通信，实现虚拟机内的线速率数据包处理。这种灵活的基础设施将允许根据复杂的策略、数据包数据或服务状态重定向数据包，这在目前基于硬件的解决方案中是不可能的。第二个重点领域是云计算数据中心，其中SDNFV将使云数据中心运营商能够以与当前虚拟化服务器和存储设备相同的方式轻松分区和复用网络资源。在这个应用领域，pi正在开发虚拟化层信任边界，以提供严格的性能和数据隔离，同时仍然允许SDNFV所需的优化。S快速数据包处理。他们还将研究新的资源管理和调度算法，以确保一组基于虚拟机的网络服务能够满足严格的延迟要求。最后，pi将通过构建原型并使用实际基准工作负载和跟踪测试来评估他们的想法。通过从单一用途的硬件过渡到灵活的基于软件的网络组件，拟议的工作有可能重新定义网络的构建和管理方式。这项研究可以使我们所依赖的互联数字世界更高效，对工作负载变化、攻击和政策决策的响应更快。这项研究将与一项教育计划相结合，以加强研究机构的网络和分布式系统课程。这将帮助本科生、硕士生和博士生在进入劳动力市场时，在最新的网络技术方面拥有非常抢手的经验。

Traditional computer networks have been built from hardware appliances, such as routers, firewalls, and switches, to implement functionality. These devices can process network packets at high speed, but provide little flexibility since they are based on purpose-built hardware. Recent improvements in multi-core processors and high-speed network interface cards have enabled Network Function Virtualization (NFV), which allows these network components to run instead on commodity compute servers. NFV makes the network data processing elements run as software, allowing them to be deployed dynamically or easily modified and tuned with changes in network workloads. At the same time, Software Defined Networking (SDN) has grown in popularity as a way to manage more easily network services by centralizing control plane functions. This research investigates how the convergence of NFV and SDN can enable a new breed of highly dynamic network services for customers of Internet Service Providers (ISPs), and also grant cloud computing customers far greater control over data center resources. The work will explore both the software mechanisms needed to support network components running at speeds well beyond 10 Gbps inside of virtual machines, and the algorithms and control architectures required to coordinate these components with high performance and low cost. The project targets two application areas for Software Defined Network Function Virtualization (SDNFV). The first is dynamic services for network providers for which the principal investigators (PIs) are developing a SDNFV platform that enables line-rate packet processing within virtual machines by exploiting network interface controller (NIC) polling and shared memory for zero-copy communication. This flexible infrastructure will allow packets to be redirected based on complex policies, packet data, or service state, which is not currently possible in hardware-based solutions. The second focus area is on cloud computing data centers in which SDNFV will enable cloud data center operators to easily partition and multiplex network resources in the same way they currently virtualize servers and storage devices. In this application area the PIs are developing virtualization-layer trust boundaries that provide strict performance and data isolation, while still permitting the optimizations required for SDNFV?s fast packet processing. They will also study the new resource management and scheduling algorithms required to ensure a group of virtual machine-based network services can meet their strict latency requirements. Finally the PIs will evaluate their ideas by building prototypes and testing them using realistic benchmark workloads and traces.The proposed work has the potential to redefine how networks are built and managed, by transitioning away from single-purpose hardware to flexible software-based network components. This research could make the connected, digital world we rely on more efficient and more responsive to workload changes, attacks, and policy decisions. The research will be paired with an educational program to enhance the networking and distributed systems curriculum at the researchers' institutions. This will help prepare undergraduate, Masters, and Ph.D. students to enter the work force with highly sought-after experience in the latest networking technologies.