CRI: CI-EN: Collaborative Research: OpenNetVM: A Software Platform Enabling Network Function Virtualization Research

CRI：CI-EN：协作研究：OpenNetVM：支持网络功能虚拟化研究的软件平台

• 批准号: 1823270
• 负责人: Kadangode Ramakrishnan
• 金额: $ 32.5万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823270&HistoricalAwards=false
• 关键词: CRI; CI; EN; Collaborative; Research

Network Function Virtualization is a "disruptive" technology that changes the network from a transport pipe to a software-defined infrastructure offering flexible services. By transforming network functions to dynamically allocated software containers, new types of applications can be supported along with better network management. OpenNetVM is an open source software platform that seeks to lower the barrier for researchers wishing to explore challenges in this area, and for developers wishing to evaluate new types of network services. This project will provide a robust and flexible foundation that will enable new innovations in these areas. The principal investigators will engage the community to encourage adoption through frequent tutorials and demonstrations. Communication Networks have increasingly become `software based'. Network Function Virtualization (NFV) provides a high-performance network data plane (e.g., middleboxes like firewalls, proxies) and is currently seeing both research and industry interest. NFV research has been stymied by the inadequate software platforms that either offer only very low-level access to packet data (making it difficult to evaluate complex services), or are based on traditional packet-processing approaches that have very poor performance for current-day applicability. The researchers will maintain OpenNetVM as an open-source (BSD (Berkeley Software Distribution) license) software infrastructure, providing high-level abstractions with an underlying framework that provides wire-speed performance, primitives for scheduling, and scalability, that offers both industry and academic researchers a way to quickly and conveniently build network functions. OpenNetVM runs network functions in lightweight containers, easily combined to form complex "service chains". The project seeks to provide improved support for real middleboxes with OpenNetVM by adding user space protocol stacks enabling more complex NFs and services, substantially expanding the types of applications supported. The project also expands OpenNetVM to support many NFs that share each CPU core, and distributed deployments where NFs are spread across a cluster, thus enabling research into NFV resource management, NF placement, and complex service chaining. Finally, OpenNetVM will be extended to expose low-level performance metrics that will enable research into automated resource management platforms. To facilitate adoption the researchers will provide comprehensive documentation, tutorials at major conferences, and template images using publicly accessible resources such as NSF CloudLab. The result will be a comprehensive, open source platform that can be used broadly across the networking and operating systems communities. In addition, this project supports the training of a diverse body of students, with an emphasis on preparing a mix of undergraduate and graduate students for entering the high demand field of software-based networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

网络功能虚拟化是一种“破坏性”技术，它将网络从传输管道更改为提供灵活服务的软件定义的基础架构。通过将网络功能转换为动态分配的软件容器，可以支持新的应用程序以及更好的网络管理。 OpenNETVM是一个开源软件平台，旨在降低希望探索该领域挑战的研究人员以及希望评估新类型网络服务的开发人员的障碍。该项目将提供一个强大而灵活的基础，该基础将在这些领域提供新的创新。主要调查人员将通过频繁的教程和示威活动来吸引社区，以鼓励采用。通信网络已越来越成为基于软件的”。网络功能虚拟化（NFV）提供了高性能的网络数据平面（例如，诸如防火墙，代理等中间箱），目前正在看到研究和行业兴趣。 NFV研究受到不足的软件平台的困扰，这些平台仅提供非常低水平的数据包数据访问（使得很难评估复杂服务），或者基于传统的数据包处理方法，这些方法的性能较差，无法实现当前的适用性。研究人员将维持OpenNETVM作为开源（BSD（Berkeley软件分销））软件基础架构，以提供高级抽象的基础框架，其基础框架可提供电线速度性能，用于调度的原始性和可扩展性，可为行业和学术研究人员提供快速且方便地构建网络功能的方式。 OpenNETVM在轻质容器中运行网络功能，易于组合形成复杂的“服务链”。该项目旨在通过添加启用更复杂的NFS和服务的用户空间协议堆栈来提供对带有OpenNETVM的真实中间箱的改进支持，从而大大扩展了支持的应用程序类型。该项目还扩展了OpenNETVM，以支持许多共享每个CPU核心的NF，并分布了NFS分布在集群中的部署，从而可以研究NFV资源管理，NF安置和复杂的服务链条。最后，OpenNETVM将扩展以揭示低级性能指标，以使自动化资源管理平台进行研究。为了促进采用，研究人员将使用公开访问的资源（例如NSF CloudLab）提供全面的文档，主要会议的教程以及模板图像。结果将是一个全面的开源平台，可以在整个网络和操作系统社区中广泛使用。 此外，该项目支持培训各种各样的学生，并着重于准备本科生和研究生的组合，以进入基于软件的网络的高需求领域。这项奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查审查的审查标准来通过评估来通过评估来支持的。

项目成果

MiddleNet: A High-Performance, Lightweight, Unified NFV and Middlebox Framework

MiddleNet：高性能、轻量级、统一的 NFV 和 Middlebox 框架

• DOI: 10.1109/netsoft54395.2022.9844083
• 发表时间: 2022
• 期刊: 2022 IEEE 8th International Conference on Network Softwarization (NetSoft
• 作者: Zeng, Ziteng;Monis, Leslie;Qi, Shixiong;Ramakrishnan, K. K.
• 通讯作者: Ramakrishnan, K. K.

Synergy: A SmartNIC Accelerated 5G Dataplane and Monitor for Mobility Prediction

• DOI: 10.1109/icnp55882.2022.9940261
• 发表时间: 2022-10
• 期刊: 2022 IEEE 30th International Conference on Network Protocols (ICNP)
• 作者: Sourav Panda;K. Ramakrishnan;L. Bhuyan

Evolving to 6G: Improving the Cellular Core to lower control and data plane latency

演进到 6G：改进蜂窝核心以降低控制和数据平面延迟

• DOI: 10.1109/6gnet54646.2022.9830519
• 发表时间: 2022
• 作者: Jain, Vivek;Panda, Sourav;Qi, Shixiong;Ramakrishnan, K. K.
• 通讯作者: Ramakrishnan, K. K.

Managing State for Failure Resiliency in Network Function Virtualization

管理网络功能虚拟化中的状态以实现故障恢复

• DOI: 10.1109/lanman49260.2020.9153271
• 发表时间: 2020
• 期刊: 2020 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN
• 作者: Kulkarni, Sameer G;Ramakrishnan, K. K.;Wood, Timothy
• 通讯作者: Wood, Timothy

X-IO: A High-performance Unified I/O Interface using Lock-free Shared Memory Processing

X-IO：使用无锁共享内存处理的高性能统一 I/O 接口

• DOI: 10.1109/netsoft57336.2023.10175428
• 发表时间: 2023
• 期刊: 2023 IEEE 9th International Conference on Network Softwarization (NetSoft
• 作者: Qi, Shixiong;Tsai, Han-Sing;Liu, Yu-Sheng;Ramakrishnan, K. K.;Chen, Jyh-Cheng
• 通讯作者: Chen, Jyh-Cheng