Distributed Core Decomposition in Probabilistic Graphs

  • Qi Luo
  • Dongxiao YuEmail author
  • Feng LiEmail author
  • Zhenhao Dou
  • Zhipeng Cai
  • Jiguo YuEmail author
  • Xiuzhen Cheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11917)


This paper initializes distributed algorithm studies for core decomposition in probabilistic graphs. Core decomposition has been proven to be a useful primitive for a wide range of graph analyses, but it has been rarely studied in probabilistic graphs, especially in a distributed environment. In this work, under a distributed model underlying Pregel and live distributed systems, we present the first known distributed solutions for core decomposition in probabilistic graphs, where there is an existence probability for each edge. In the scenario that the existence probability of edges are known to nodes, the proposed algorithm can get the exact coreness of nodes with a high probability guarantee. In the harsher case that the existence probability is unknown, we present a novel method to estimate the existence probability of edges, based on which the coreness of nodes with small approximation ratio guarantee can be computed. Extensive experiments are conducted on different types of real-world graphs and synthetic graphs. The results illustrate that the proposed algorithms exhibit good efficiency, stability and scalability.


Uncertain graph Core decomposition Distributed algorithm 



This work is partially supported by NSFC (No. 61971269, 61832012, 61672321, 61771289, 61702304) and Shandong Provincial Natural Science Foundation (No. ZR2017QF005).


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Authors and Affiliations

  1. 1.School of Computer Science and TechnologyShandong UniversityQingdaoPeople’s Republic of China
  2. 2.Department of Computing ScienceGeorgia State UniversityAtlantaUSA
  3. 3.School of Computer Science and TechnologyQilu University of TechnologyJinanPeople’s Republic of China

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