NeTS:Small:Dynamic Coupling and Flow-Level Performance in Data Networks: From Theory to Practice

NeTS:Small：数据网络中的动态耦合和流级性能：从理论到实践

• 批准号: 0917067
• 负责人: Gustavo de Veciana
• 金额: $ 40万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0917067&HistoricalAwards=false
• 关键词: NeTS; Small; Dynamic; Coupling; Flow

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The performance of network users' best effort flows, e.g., file transfer delays and web browsing responsiveness, depends on the resources they are allocated over time. When varying traffic loads share these resources and/or wireless nodes' transmission capacities depend on each other through interference, the allocated resources and thus flows' performance are coupled through the traffic and interference dynamics. This project investigates such performance coupling in data networks and, in turn, how it affects protocol and network design. This is a significant problem, as most data networks share these characteristics, and we currently have no robust tools to effectively predict and thus optimize performance. Expected results include new theory, approximations and performance bounds enabling the analysis of such systems which are also applicable to other domains. Expected results also include using these tools to investigate: (1) the benefits of, and capacity allocation, in networks supporting multipath transport and/or shared wireless access networks; and (2), the development of improved protocols and algorithms that are sensitive to such performance coupling, e.g., preliminary work suggests the state-of-the-art base station association policies can be substantially improved by factoring the performance coupling resulting form interference. The work's impact will be assured through broad dissemination in the research community, and by leveraging industry partners in evaluating practical applications and technology transfer opportunities.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。网络用户的最佳努力流的表现，例如，文件传输延迟和Web浏览响应取决于它们随时间分配的资源。当变化的业务负载共享这些资源和/或无线节点的传输容量通过干扰彼此依赖时，所分配的资源以及因此流的性能通过业务和干扰动态耦合。 本项目研究数据网络中的这种性能耦合，以及它如何影响协议和网络设计。 这是一个重要的问题，因为大多数数据网络都具有这些特征，而且我们目前还没有强大的工具来有效地预测并优化性能。 预期结果包括新的理论，近似和性能界限，使这种系统也适用于其他领域的分析。 预期的结果还包括使用这些工具来调查：（1）在支持多路径传输和/或共享无线接入网络的网络中的益处和容量分配;以及（2）开发对这种性能耦合敏感的改进的协议和算法，例如，初步工作表明，通过将由干扰导致的性能耦合因素考虑在内，可以实质上改进现有技术的基站关联策略。将通过在研究界广泛传播，并通过利用工业伙伴评估实际应用和技术转让机会，确保这项工作的影响。