AitF: FULL: Collaborative Research: Practical Foundations for Software-Defined Network Optimization

当今社会严重依赖互联网服务。这些互联网服务的安全性和性能反过来又依赖于单个网络成功的能力。管理和优化他们的网络配置，以应对不断变化的操作环境（例如，流量或攻击的突然增加或策略遵从性需求的变化）。如今，网络运营商经常采用影响网络安全和性能的临时和脆弱的解决方案。本计画的目标是结合理论与实务，发展基本机制，使网路管理员能够执行不同的网路作业任务。该项目将开发抽象，用于表达广泛的网络优化任务和算法基础，以推理并实现优于当前最优（或接近最优）的解决方案。, # 8203;该项目将开发和发布开源工具包，这些工具包将大大减少原型化和部署新型网络管理应用程序的时间，并为更多的受众普及这些好处。该项目将推动教育进步，通过将理论与实践相结合的变革性研究，帮助培养能够应对未来技术挑战的全面劳动力。该项目将积极鼓励代表性不足的群体参与，作为拟议工作的一部分，并指导他们成为未来的技术领导者。软件定义网络（SDN）是一种新兴的范例，它通过将嵌入在网络硬件配置中的策略移动到运行在集中控制器中的软件中来简化网络管理。然而，实现SDN的潜在优势目前需要大量的理论和实践努力。具体来说，许多SDN应用程序的核心是复杂的优化问题，以解决实践中出现的目标和需求。这些问题都没有好的理论解决方案。该项目的目标是设计和实现一个新颖的框架，使SDN应用程序开发人员能够用高级语言表达新的应用程序目标和约束，使用健全的算法方法生成接近最优的解决方案，然后生成可直接部署到SDN控制平台的兼容配置。要想在实践中成功实现这一愿景，有两个要求：(i)能够表达广泛应用程序的需求，以及（ii）在响应应用程序需求的时间尺度上生成可证明的最优（或接近最优）配置。本研究将探讨理论基础与实务实施，以同时达成这两个目标。该项目的贡献将包括：(1)研究基于路径的优化对广泛的SDN应用程序的鲁棒性，并开发算法以确保这种基于路径的重新制定不会牺牲效率；(2)为需要更多动态网络处理特性的应用程序设计更丰富的抽象，并为这些应用程序开发接近最优和实用的算法；(3)设计有效的优化——保留从这些理论框架到实际网络配置的解决方案的转换；(4)在与最先进的网络管理平台集成的端到端开源工具中实现这些技术。

Society today critically depends on Internet services. The safety and performance of these Internet services in turn depends on the ability of individual networks to successfully​ manage and optimize their network configurations in reaction to a changing operating environment (e.g., sudden increases in traffic or attacks or changes in policy compliance requirements). Today, network operators often resort to ad hoc and brittle solutions that affect the safety and performance of the networks. The goal of this project is combine theory and practice to develop foundational mechanisms enabling network administrators to implement diverse network operations tasks. This project will develop abstractions for expressing a broad spectrum of network optimization tasks and algorithmic foundations to reason about and achieve optimal (or near-­optimal) solutions that will be better than current state-of-the-art. ​The project will develop and release open­-source toolkits that will dramatically reduce the time to prototype and deploy novel network management applications, and democratize these benefits for a larger audience. The project will lead to educational advances that help create a well­-rounded workforce capable of handling future technology challenges by applying transformational research that couples theory and practice. The project will actively encourage participation from underrepresented groups as part of the proposed work and mentor them to be future technology leaders.Software-­defined networking (SDN) is an emerging paradigm to simplify network management by moving policies embedded in the configurations of the network hardware to software running in centralized controllers. Realizing the potential benefits of SDN, however, currently requires significant theoretical and practical effort. Specifically, at the core of many SDN applications are complex optimization problems to tackle goals and requirements that arise in practice. These problems are ones for which good theoretical solutions are unknown.The goal of this project is to design and implement a novel framework that enables SDN application developers to express new application goals and constraints in a high-­level language, using a sound algorithmic approach to generate near­-optimal solutions, and then to generate compliant configurations that can be deployed to SDN control platforms directly. There are two requirements for this vision to be successful in practice: (i) the ability to express the requirements of a broad spectrum of applications and (ii)­­ generating provably optimal (or close ­to ­optimal) configurations, on a timescale that is responsive to application needs. The proposed research will investigate theoretical foundations and practical implementations to simultaneously achieve both goals. The project's contributions will include: (1) investigating the robustness of path-­based optimizations for a wide spectrum of SDN applications and developing algorithms for ensuring that such path­-based reformulations do not sacrifice efficiency; (2) designing richer abstractions for applications that require more dynamic network processing features and developing near­-optimal and practical algorithms for these applications; (3) designing efficient optimization-­preserving translations of solutions from such theoretical frameworks into practical network configurations; and (4) implementing these techniques in an end­-to-­end open-­source tool integrated with state­-of-­the-­art network management platforms.