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

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
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1994
资助国家:
美国
项目状态:
已结题
起止时间:
1994-06-01 至 1998-05-31

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英文摘要
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.
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  • 资助金额:
    $30.0万
  • 财政年份:
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RINGS: Scalable and Resilient Networked Learning Systems
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    2148224
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $63.0万
  • 财政年份:
    2022
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CNS Core: Small: Online Safe Reinforcement Learning for Wireless Resource Allocation
  • 批准号:
    1910112
  • 项目类别:
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  • 资助金额:
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    2019
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  • 批准号:
    1809327
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
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  • 负责人:
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