NeTS: Small: Managing Network Function Virtualization under Uncertainty

NeTS：小型：在不确定性下管理网络功能虚拟化

• 批准号: 1717493
• 负责人: Xiaojun Lin
• 金额: $ 50万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1717493&HistoricalAwards=false
• 关键词: NeTS; Small; Managing; Network; Function

Data centers are increasingly virtualizing network functions that have been traditionally implemented as hardware appliances. Today's network functions (such as firewalls and multimedia support systems) are costly to procure, deploy, and change. With virtualization, these network functions can instead be implemented as software running on low cost commodity servers. Their placement, size and connectivity can be adjustable on-demand though management and orchestration systems.This project seeks to develop the theoretic foundations and practical implementations to achieve provably efficient, low-cost, and robust Network Function Virtualization (NFV) operation in dynamic and uncertain environments. The project will develop online algorithms for placing, scaling and migrating virtualized network functions that take uncertain future network traffic and compute workloads into consideration. The investigators will model the variability and uncertainty of the compute load and network traffic in a rigorous mathematical framework to develop control algorithms with provable guarantees in cost and performance. The three principal research activities are: 1) exploring online NFV orchestration and scaling under uncertainty; 2) managing end-to-end queueing performance under uncertainty and cross-function dependency; and 3) designing algorithms and analyzing key performance and complexity bottlenecks.

数据中心正在越来越多地虚拟化传统上作为硬件设备实现的网络功能。 当今的网络功能（如防火墙和多媒体支持系统）的采购、部署和更改成本都很高。通过虚拟化，这些网络功能可以作为在低成本商品服务器上运行的软件来实现。该项目旨在开发理论基础和实际实现，以实现动态和不确定环境中可证明有效，低成本和鲁棒的网络功能虚拟化（NFV）操作。 该项目将开发用于放置、扩展和迁移虚拟化网络功能的在线算法，这些算法将不确定的未来网络流量和计算工作负载考虑在内。研究人员将在严格的数学框架中对计算负载和网络流量的可变性和不确定性进行建模，以开发具有可证明的成本和性能保证的控制算法。三个主要研究活动是：1）探索不确定性下的在线NFV编排和扩展; 2）管理不确定性和跨功能依赖性下的端到端调度性能; 3）设计算法并分析关键性能和复杂性瓶颈。

项目成果

Experience: towards automated customer issue resolution in cellular networks

经验：在蜂窝网络中实现自动化客户问题解决

• DOI: 10.1145/3372224.3419203
• 发表时间: 2020
• 期刊: United Kingdom
• 作者: Sheoran, Amit;Fahmy, Sonia;Osinski, Matthew;Peng, Chunyi;Ribeiro, Bruno;Wang, Jia
• 通讯作者: Wang, Jia

Combining Regularization with Look-Ahead for Competitive Online Convex Optimization

• DOI: 10.1109/infocom42981.2021.9488766
• 发表时间: 2021-05
• 期刊: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications
• 作者: Ming Shi;Xiaojun Lin;Lei Jiao

Data-driven resource flexing for network functions visualization

• DOI: 10.1145/3230718.3230725
• 发表时间: 2018-07
• 期刊: Proceedings of the 2018 Symposium on Architectures for Networking and Communications Systems
• 作者: Lianjie Cao;S. Fahmy;P. Sharma;Shandian Zhe

Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations

• DOI: 10.1609/aaai.v34i04.5806
• 发表时间: 2020-02
• 作者: Jianfei Gao;Mohamed Zahran;Amit Sheoran;S. Fahmy;Bruno Ribeiro

RoCC: robust congestion control for RDMA

• DOI: 10.1145/3386367.3431316
• 发表时间: 2020-11
• 期刊: Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies
• 作者: Parvin Taheri;Danushka Menikkumbura;E. Vanini;S. Fahmy;P. Eugster;T. Edsall