FIND: Collaborative Research: Towards An Analytic Foundation for Network Architectures

在大型复杂的通信网络中，关于功能分配的架构决策通常比资源分配算法本身的细节更重要。这个NSF资助的项目旨在通过建立在最近成功理解协议作为优化器和分层作为数学分解的基础上，为设计网络架构奠定科学基础。特别是，在五个机构的PI合作进行广泛的紧密相连的研究活动，大大提高了国家的最先进的。从一个凸优化制定的架构设计问题，该项目调查了广泛的替代分解，提供不同的可扩展性，收敛性和复杂性的权衡。PI然后确定这些替代架构的属性是否继续保持随机网络动态和非凸目标和约束下，并开发新的架构设计从这样的动态仔细研究。在数学上，该项目将网络优化和随机网络理论结合起来，并为利用一般非凸优化的进步提供了一种系统的方法。更广泛的影响：该项目与NSF的GENI计划具有明显的协同作用。该研究为未来网络架构的设计提供了强大的分析基础，包括偏离当今互联网的干净的解决方案。探索新的方法来分解功能，考虑到网络动态和非凸性的影响，将导致新的协议和机制，可以在GENI基础设施进行评估。

In large and complex communication networks, architectural decisions regarding functionality allocation are often more important than the details of resource allocation algorithms themselves. This NSF-funded project aims to develop a scientific foundation for designing network architectures by building upon recent successes in understanding protocols as optimizers and layering as mathematical decompositions. In particular, the PIs at five institutions collaborate to conduct a wide range of closely-connected research activities that substantially improve upon the state-of-the-art. Starting from a convex optimization formulation of the architecture design problem, the project investigates a wide range of alternative decompositions that provide different scalability, convergence, and complexity tradeoffs. The PIs then determine whether the properties of these alternative architectures continue to hold under stochastic network dynamics and non-convex objectives and constraints, and develop new architectural designs from a careful study of such dynamics. Mathematically, this project leads to a long-overdue union between network optimization and stochastic networks theory, and enables a systematic approach to leverage advances in general non-convex optimization.Broader Impact: This project has clear synergy with the NSF's GENI initiative. The research provides a strong, analytic foundation for the design of future network architectures, including clean-slate solutions that deviate from todays Internet. The exploration of new ways to decompose functionality, with the influence of network dynamics and non-convexity in mind, will result in new protocols and mechanisms that can be evaluated in the GENI infrastructure.