NeTS: Small: Managing Network Function Virtualization under Uncertainty

数据中心越来越多地将传统上作为硬件设备实现的网络功能虚拟化。今天的网络功能（如防火墙和多媒体支持系统）的采购、部署和更改成本很高。通过虚拟化，这些网络功能可以作为运行在低成本商用服务器上的软件来实现。它们的位置、大小和连接性可以通过管理和编排系统按需调整。该项目旨在发展理论基础和实际实现，以在动态和不确定环境中实现可证明的高效、低成本和健壮的网络功能虚拟化（NFV）操作。该项目将开发用于放置、扩展和迁移虚拟网络功能的在线算法，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)不确定和跨功能依赖下的端到端队列性能管理；3)算法设计，关键性能和复杂度瓶颈分析。

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.