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AF: Small: Distributed Algorithms for Near-Planar Networks

AF: Small: Distributed Algorithms for Near-Planar Networks
AF:小型:近平面网络的分布式算法
批准号:
1527110
负责人:
Bernhard Haeupler
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-06-15 至 2018-05-31

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中文摘要
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英文摘要
The goal of this project is the development of an algorithmic toolbox to design efficient distributed algorithms for planar and near-planar networks. (Informally, a planar network is one that can be drawn on a two-dimensional surface without any lines crossing.) Many real-world networks and optimization problem instances have a near-planar structure that allows for simpler, more efficient, and often more practical algorithms. The study of such network structures and their algorithmic implications has been a very successful endeavor with a rich theory, many versatile tools, significant algorithmic advances, and drastic performance improvements on problem instances of interest. While modern systems become increasingly larger and more distributed, little is known about how distributed algorithms can be improved on near-planar instances. This project aims to change this and to bring similar improvements to the distributed setting. While its scope is primarily theoretical, the algorithms and general principles to be developed have the potential of laying the groundwork for practical algorithms with real-world impacts. The project will also have a broad educational impact. Much of the research will be done by or in collaboration with graduate students. Furthermore, the proposed research direction features many theoretical questions suitable for undergraduate students without extensive background knowledge and also provides opportunities for experiments and implementation projects. Lastly, the interdisciplinary nature of the problem will likely foster many collaborations between the PI and other researchers in different fields. Any tools and algorithms developed will be shared publicly.This project will initiate the principled study of distributed algorithms for planar and near-planar networks. In particular, for networks with diameter D and standard bandwidth-limitations (CONGEST model), the project aims at obtaining efficient distributed algorithms running in O(D) synchronous rounds for important standard optimization problems like maximum flow, minimum spanning tree, and various shortest path problems. This approach very timely connects to recent, far-reaching, distributed lower bounds which show that in general (sparse) graphs many optimization problems cannot be computed or even crudely approximated in less than Omega(sqrt(n))-rounds. The PI believes that this proposal provides an exciting new direction for the theory of distributed network optimization algorithms and gives a new perspective on the algorithmic study of planar and near-planar graphs. The expectation is that this broader research direction and the concrete initial results coming out of this project will spark the interest of the community and serve as a basis for a larger and more extensive investigation.
期刊论文(32)
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会议论文
DOI: 10.1109/focs46700.2020.00053
发表时间: 2019-05
期刊: 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS)
影响因子: --
作者: [Bernhard Haeupler;David Wajc;Goran Zuzic]
通讯作者: Bernhard Haeupler;David Wajc;Goran Zuzic
Making Asynchronous Distributed Computations Robust to Noise
使异步分布式计算对噪声具有鲁棒性
DOI: 10.4230/lipics.itcs.2018.50
发表时间: 2018
期刊: ACM-SIGACT Innovations in Theoretical Computer Science Conference
影响因子: --
作者: [Censor-Hillel, Keren, Gelles, Ran, Haeupler, Bernhard]
通讯作者: Haeupler, Bernhard
Minor Excluded Network Families Admit Fast Distributed Algorithms
少数被排除在外的网络家族承认快速分布式算法
DOI: 10.1145/3212734.3212776
发表时间: 2018
期刊: ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing
影响因子: --
作者: [Haeupler, Bernhard, Li, Jason, Zuzic, Goran]
通讯作者: Zuzic, Goran
DOI: 10.1137/1.9781611976465.1
发表时间: 2020-07
期刊:
影响因子: --
作者: [Kuan Cheng;V. Guruswami;Bernhard Haeupler;Xin Li]
通讯作者: Kuan Cheng;V. Guruswami;Bernhard Haeupler;Xin Li
29
    AF: Small: Distributed Optimization Beyond Worst Case Topologies
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    • 项目类别:
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    • 资助金额:
      $45.0万
    • 财政年份:
      2016
    • 负责人:
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    • 依托单位:
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    • 资助金额:
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