TF:SING: Exploring the Fundamental Limits of Cross-Layer Optimization in the Next-Generation Internet

TF:SING：探索下一代互联网跨层优化的基本极限

• 批准号: 0830493
• 负责人: Song Ci
• 金额: $ 17.17万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0830493&HistoricalAwards=false
• 关键词: TF; SING; Exploring; Fundamental; Limits

Although there has been a considerable amount of research done by using cross-layer optimization, fundamental understandings on the design limits of cross-layer optimization are still missing. The overarching goal of this project is to fill this knowledge gap. The objectives are to 1) qualitatively characterize multi-scale temporal-spatial behaviors of cross-layer optimization; 2) develop a novel complexity-scalable framework to support cross-layer optimization over heterogeneous network elements with different computation capabilities; and 3) evaluate the proposed framework by using extensive simulations as well as field test based on our existing testbed.The intellectual merits and transformative significance of this project include: 1) to provide a theoretical framework to understand major design tradeoffs in cross-layer design and optimization and 2) to provide a common ground to quantitatively evaluate and compare different cross-layer design schemes. By developing a new theoretical framework to quantitatively analyze design tradeoffs in complex system optimization, the broader impacts of this project are: 1) to benefit wide applications in social networks, economics, physics, and biology, leading to a profound impact on all societal levels and 2) to expand the existing collaborations with industrial partners and enhance the ongoing effort on STEM education. Results, outcomes, software tools, benchmarks, and educational materials will be disseminated through a project?s web site as well as journal and conference publications. The research results of cross-layer optimizations will also be integrated into courses taught in the PI's university.

尽管通过使用跨层优化进行了大量研究，但仍然缺少对跨层优化设计限制的基本理解。该项目的总体目标是填补这一知识差距。目标是1）定性表征跨层优化的多尺度时间空间行为； 2）开发一个新型的复杂性尺度框架，以支持具有不同计算功能的异质网络元素上的跨层优化； 3）通过使用广泛的模拟以及基于我们现有的测试床的现场测试来评估所提出的框架。该项目的智力优点和变革意义包括：1）提供一个理论框架，以了解跨层设计中的主要设计权衡。和优化和2）提供了一个共同的基础，以定量评估和比较不同的跨层设计方案。通过开发一个新的理论框架来定量分析复杂系统优化的设计权衡，该项目的更广泛影响是：1）使社交网络，经济学，物理学和生物学中的广泛应用受益，从而对所有社会层面产生深远的影响2）扩大与工业伙伴的现有合作，并增强对STEM教育的持续努力。结果，结果，软件工具，基准和教育材料将通过项目网站以及日记和会议出版物进行传播。跨层优化的研究结果也将集成到PI大学教授的课程中。