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Faster Parallel Core Maintenance Algorithms in Dynamic Graphs

机译:动态图中更快的并行核心维护算法

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摘要

This article studies the core maintenance problem for dynamic graphs which requires to update each vertex's core number with the insertion/deletion of vertices/edges. Previous algorithms can either process one edge associated with a vertex in each iteration or can only process one superior edge associated with the vertex (an edge 〈u; v〉 is a superior edge of vertex u if v' core number is no less than u's core number) in each iteration. Thus for high superior-degree vertices (the vertices associated with many superior edges) insertions/deletions, previous algorithms become very inefficient. In this article, we discovered a new structure called joint edge set whose insertions/deletions make each vertex's core number change at most one. The joint edge set mainly contains all the superior edges associated with the high superior-degree vertices as long as these vertices are 3+-hop independent. Based on this discovery, faster parallel algorithms are devised to solve the core maintenance problems. In our algorithms, we can process all edges in the joint edge set in one iteration and thus can greatly increase the parallelism and reduce the processing time. The results of extensive experiments conducted on various types of real-world, temporal, and synthetic graphs illustrate that the proposed algorithms achieve good efficiency, stability and scalability. Specifically, the new algorithms can outperform the single-edge processing algorithms by up to four orders of magnitude. Compared with the matching based algorithm and the superior edge based algorithm, our algorithms show a significant speedup up to 60× in the processing time.
机译:本文研究了动态图形的核心维护问题,需要使用插入/删除顶点/边缘更新每个顶点的核心号。先前的算法可以处理与每次迭代中的顶点相关联的一个边缘,或者只能处理与顶点相关联的一个优越的边缘(边缘是顶点U的高级边缘,如果V'核心号码不小于U's核心号码)在每次迭代中。因此,对于高级度的顶点(与许多优越边缘相关的顶点)插入/删除,先前的算法变得非常低效。在本文中,我们发现了一种称为联合边缘集的新结构,其插入/删除使每个顶点的核心号最多一个。关节边缘设定主要包含与高级度顶点相关联的所有上边缘,只要这些顶点为3即可 + -HOP独立。基于此发现,设计了更快的并行算法以解决核心维护问题。在我们的算法中,我们可以在一个迭代中处理联合边缘中的所有边缘,从而大大增加并行性并减少处理时间。在各种类型的现实世界,时间和合成图中进行了广泛实验的结果说明了所提出的算法实现良好的效率,稳定性和可扩展性。具体地,新算法可以优于单边缘处理算法,最多四个级别。与基于匹配的算法和卓越的基于校长的算法相比,我们的算法在处理时间内显示出高达60倍的显着加速。

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  • 作者单位

    National Engineering Research Center-Big Data Technology and System Lab Key Laboratory of Services Computing Technology and System Key Laboratory of Cluster and Grid Computing School of Computer Science and Technology Huazhong University of Science and Technology Wuhan P.R. China;

    National Engineering Research Center-Big Data Technology and System Lab Key Laboratory of Services Computing Technology and System Key Laboratory of Cluster and Grid Computing School of Computer Science and Technology Huazhong University of Science and Technology Wuhan P.R. China;

    School of Computer Science and Technology Shandong University Qingdao P.R. China;

    National Engineering Research Center-Big Data Technology and System Lab Key Laboratory of Services Computing Technology and System Key Laboratory of Cluster and Grid Computing School of Computer Science and Technology Huazhong University of Science and Technology Wuhan P.R. China;

    School of Computer Science and Technology Shandong Academy of Sciences Jinan Shandong P.R. China;

    Department of Computer Science Georgia State University Atlanta GA USA;

    School of Computer Science and Technology Shandong University Qingdao P.R. China;

    National Engineering Research Center-Big Data Technology and System Lab Key Laboratory of Services Computing Technology and System Key Laboratory of Cluster and Grid Computing School of Computer Science and Technology Huazhong University of Science and Technology Wuhan P.R. China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Maintenance engineering; Heuristic algorithms; Multicore processing; Parallel algorithms; Computer science; Indexes; Stability analysis;

    机译:维护工程;启发式算法;多核加工;并行算法;计算机科学;索引;稳定性分析;

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