Collaborative Research: Towards An Analytic Foundation for Network Architectures

协作研究：建立网络架构的分析基础

• 批准号: 0635202
• 负责人: Xiaojun Lin
• 金额: --
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-10-01 至 2008-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0635202&HistoricalAwards=false
• 关键词: Collaborative; Research; Towards; Analytic; Foundation

In large and complex communication networks, architectural decisions regarding functionality allocation are extremely important. The time is ripe for building a scientific foundation for network architectures, both to capitalize on unique clean-slate design opportunities (such as GENI and MANET) and to guide the evolution from existing network architectures to new ones. Such a foundation can lead to highly efficient, robust, and scalable protocols that could have a significant impact on the communications industry.The recent successes of understanding protocols as optimizers and layering as mathematical decompositions offer a promising starting point for such an analytic foundation one that is conceptually unifying, mathematically rigorous, and practically relevant. However, there is still much work to be done in developing an analytic foundation for network architectures. This research focuses on three main thrusts: Alternative architectural choices: Past mathematical results have focused on one architecture derived from a particular decomposition. There is in fact a wide range of alternative decompositions that result in different scalability, convergence, and complexity tradeoffs. This research systematically explores architectural choices using appropriate decompositions.Stochastic network dynamics: This research develops new architectural designs taking into account stochastic (rather than deterministic) network dynamics, which are critical in modeling real systems and in developing high-performance network architectures. Non-convexity and robustness: Non-convexity persists in real networks, which could lead to instability, poor performance, and impractical computational complexity. Nonetheless, most past results have been derived only for the convex case. This research explores architectural choices that are robust to non-convexity.

在大型且复杂的通信网络中，有关功能分配的架构决策极为重要。现在是为网络体系结构建立科学基础的时机，既可以利用独特的清洁式设计机会（例如GENI和Manet），并指导从现有网络体系结构到新的架构的演变。 这样的基础可以导致高效，稳健和可扩展的协议，这些协议可能会对通信行业产生重大影响。理解作为优化者和分层作为数学分解的协议的最新成功为这种分析基础提供了一个有希望的起点，该基础基础是善于统一的，数学上严格，并且在数学上是与之相关的。但是，在建立网络体系结构的分析基础方面，仍有很多工作要做。这项研究侧重于三个主要推力：替代体系结构选择：过去的数学结果集中在一种源自特定分解的体系结构上。实际上，有广泛的替代分解会导致不同的可扩展性，收敛性和复杂性权衡。这项研究系统地使用适当的分解来系统地探索建筑选择。结构网络动态：该研究考虑了随机（而不是确定性）网络动态的新建筑设计，这对于对真实系统建模和开发高性能网络架构至关重要。非跨性别和鲁棒性：实际网络中的非跨性别性持续存在，这可能导致不稳定性，性能差和不切实际的计算复杂性。尽管如此，大多数过去的结果仅是针对凸情况的。这项研究探讨了稳健至非凸度的建筑选择。