Collaborative Research: NEDG: Network Scheduling and Routing under Partial Information Structure
Collaborative Research: NEDG: Network Scheduling and Routing under Partial Information Structure
批准号:
0831580
负责人:
Constantine Caramanis
金额:
$9.82万
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
项目状态:
已结题
起止时间:
2008-09-01 至 2011-08-31
中文摘要
尽管无线网络在公共、商业和政府领域取得了明显的成功,但最近的研究表明,糟糕的路由/调度会严重损害它们的性能。我们注意到,观察到的不可接受的性能损失不是文献中调度/路由算法缺乏或不足的结果;相反,原因是这些算法所假定的信息结构(通道状态、队列状态、拓扑结构等)。这一建议引导了一条不同的道路,开始了一个概念上的转变,即信息结构的首要重要性。我们考虑的实际场景中,只有一小部分的网络状态可以探索。本提案的目标是双重的:(a)描述部分/延迟网络状态信息(NSI)对网络吞吐量和其他性能指标(如延迟和可靠性)的基本影响,以及(b)开发高性能和分布式算法,可以根据部分信息进行最佳操作。更广泛的影响:我们相信这项工作可以为进一步设计具有有限NSI的高性能调度和路由所需的基础网络科学做出贡献。我们还计划将其中一些问题作为有趣的本科项目,以及开发一门新的研究生水平的通信网络设计数学课程。
英文摘要
Despite the clear success stories of wireless networks in the public, commercial, and governmental realms, recent work has shown that poor routing/scheduling can significantly impair their performance. We note that the unacceptable performance loss observed is not a consequence of a lack or deficiency of scheduling/routing algorithms in the literature; rather the cause is the information structure (channel state, queue state, topology, etc) that these algorithms assume. This proposal steers down a different path, initiating a conceptual shift toward the primary importance of information structure. We consider practical scenarios where only a small fraction of the network state can be explored. The goals of this proposal are two-fold: (a) characterizing the fundamental impact of partial/delayed network state information (NSI) on network throughput and other performance metrics such as delay and reliability, and (b) developing high-performance and distributed algorithms that can operate optimally subject to partial information. Broader Impact: We believe this work can contribute towards furthering basic network science required to design high-performance scheduling and routing with limited NSI. We also plan to bring some of the questions both as interesting undergraduate projects, as well as develop a new graduate-level course on the mathematics of the design of communication networks.
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会议论文
EPCN: Strong Diagnoses from Weak Signals: Leveraging Network Effects for Epidemic Detection
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批准号:1609279
-
项目类别:Standard Grant
-
资助金额:$36.0万
-
财政年份:2016
-
负责人:Constantine Caramanis
-
依托单位:
CAREER: High Dimensional Statistics -- Adaptive Networks, Structure and Robustness
-
批准号:1056028
-
项目类别:Standard Grant
-
资助金额:$40.0万
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财政年份:2011
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负责人:Constantine Caramanis
-
依托单位:
国内基金
海外基金
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