论文标题

改进了分布式网络中最小算法的算法

Improved Algorithm for Min-Cuts in Distributed Networks

论文作者

Daga, Mohit

论文摘要

在本论文中,我们提出了快速确定性算法,以在分布式网络中找到小切口。为网络寻找小小的最小切割对于确保服务质量和可靠性至关重要。在整个论文中,我们使用的是Consest模型,该模型是用于设计和分析分布式网络中的算法的典型消息传递模型。我们调查了Escest模型中各种算法技术,并概述了最新结果以查找削减。我们还描述了优雅的图形理论思想,例如剪切空间和周期空间,这些思想提供了有用的直觉。 我们的贡献是一种新颖的快速算法,可以找到小切口。我们的算法依赖于本文中引入的树木和切割的新特征。我们的算法建立在几种新的算法思想之上,当我们对树木和砍伐的描述时,它可以帮助我们找到所需的最小切割。我们的新技术包括树木限制的半群功能(TRSF),一种新颖的素描技术和分层算法。 TRSF是针对生成树的定义,并基于交换性半群。这种简单而功能强大的技术有助于我们确定地找到一号(桥梁)和最佳尺寸的最佳尺寸的最佳切割。我们的素描技术采样了一个小但相关的顶点集,足以在某些情况下找到小小的切割。我们的分层算法在一个较小的子图中找到了一个较小的子图,该子图在一个分布树中的不同级别的节点旋转,并利用它们在完整的图中对最小切割做出决定。这很有趣,因为它使我们能够表明,即使对于找到Min-Cuts之类的全球属性,也可以以协调的方式利用本地信息。

In this thesis, we present fast deterministic algorithm to find small cuts in distributed networks. Finding small min-cuts for a network is essential for ensuring the quality of service and reliability. Throughout this thesis, we use the CONGEST model which is a typical message passing model used to design and analyze algorithms in distributed networks. We survey various algorithmic techniques in the CONGEST model and give an overview of the recent results to find cuts. We also describe elegant graph theoretic ideas like cut spaces and cycle spaces that provide useful intuition upon which our work is built. Our contribution is a novel fast algorith to find small cuts. Our algorithm relies on a new characterization of trees and cuts introduced in this thesis. Our algorithm is built upon several new algorithmic ideas that, when coupled with our characterization of trees and cuts, help us to find the required min-cuts. Our novel techniques include a tree restricted semigroup function (TRSF), a novel sketching technique, and a layered algorithm. TRSF is defined with respect to a spanning tree and is based on a commutative semigroup. This simple yet powerful technique helps us to deterministically find min-cuts of size one (bridges) and min-cuts of size two optimally. Our sketching technique samples a small but relevant vertex set which is enough to find small min-cuts in certain cases. Our layered algorithm finds min-cuts in smaller sub-graphs pivoted by nodes at different levels in a spanning tree and uses them to make the decision about the min-cuts in the complete graph. This is interesting because it enables us to show that even for a global property like finding min-cuts, local information can be exploited in a coordinated manner.

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