RIA: Resource Management for Networks: Service Provisioning, Flow Control, and Robustness

RIA：网络资源管理：服务配置、流量控制和稳健性

• 批准号: 9409722
• 负责人: Gustavo de Veciana
• 金额: $ 9.91万
• 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: 1994
• 资助国家: 美国
• 起止时间: 1994-06-01 至 1998-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9409722&HistoricalAwards=false
• 关键词: RIA; Resource; Management; Networks; Service

University of Texas at Austin Gustavo A. de Veciana RIA: Resource Management for Networks: Service Provisioning, Flow Control, and Robustness This focus of this work is the development of resource management schemes for communication networks. Model based approaches using effective and decoupling bandwidth constraints that guarantee both individual and aggregate quality of service requirements are investigated. The emphasis is on practical issues, as well as on understanding the accuracy of these approximations at the network level. Further study of these concepts should elucidate the impact of flow control on network capacity. Since, in practice, traffic statistics and demand may be unknown or time varying, methods for on-line estimation and control are also investigated. For example, a self-tuning rate control throttle is proposed which could in principle minimize a traffic stream's burstiness subject to a loss or delay constraint by monitoring the arrival process. This is a first step towards intelligent networks that monitor, learn, and adapt to the traffic statistics and demands. The final goal of this research is to develop comparison methods based on the "robustness" of a performance guarantee for a given traffic stream.

德克萨斯大学奥斯汀·古斯塔沃A. de Veciana RIA：网络资源管理：服务提供，流程控制和鲁棒性，这项工作的重点是开发通信网络的资源管理计划。 使用有效和解耦的基于模型的方法来保证个人和总体服务质量需求的限制。重点是实际问题，以及了解网络级别上这些近似值的准确性。 对这些概念的进一步研究应阐明流程控制对网络容量的影响。 由于实际上，交通统计和需求可能未知或时间变化，因此还研究了在线估计和控制的方法。 例如，提出了一个自我调整的速率控制油门，该节气门原则上可以通过监视到达过程来最大程度地减少交通流的爆发感或延迟约束。 这是迈向智能网络的第一步，该网络监视，学习和适应流量统计和需求。 这项研究的最终目标是根据给定流量流的性能保证的“鲁棒性”制定比较方法。