A Heuristic for Constructing Minimum Average Stretch Spanning Tree Using Betweenness Centrality

Sinchan Sengupta, Sathya Peri, Vipul Aggarwal, Ambey Kumari Gupta
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Abstract

A parameter crucial for preserving the underlying shortest path information in spanning tree construction is called stretch. It is the ratio of the distance of two nodes x and y in the spanning tree to the shortest distance between x and y in the graph. In this paper, we present a heuristic LSTree that constructs a Minimum Average Stretch Spanning Tree of an n− node undirected and unweighted graph in $\mathcal{O}$(n) rounds of the CONGEST model. We like to stress that LSTree protocol is the first use of Betweenness centrality in the construction of low stretch trees. The heuristic outperforms the current benchmark algorithm of Alon et. al. as well as other spanning tree construction techniques presently known, when tested against synthetic as well as real-world graph inputs.
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一种利用中间中心性构造最小平均伸缩生成树的启发式方法
在生成树的构造中,一个对保持底层最短路径信息至关重要的参数被称为拉伸。它是生成树中两个节点x和y的距离与图中x和y之间的最短距离的比值。在本文中,我们提出了一种启发式lstreet,它在CONGEST模型的$\mathcal{O}$(n)轮中构造了n -节点无向无权图的最小平均伸缩生成树。我们想强调的是,lstreet协议是第一个在构造低伸缩树时使用中间性中心的协议。当针对合成和现实世界的图形输入进行测试时,启发式算法优于Alon等人的当前基准算法以及其他已知的生成树构建技术。
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