Core Maintenance in Dynamic Graphs: A Parallel Approach Based on Matching

The core number of vertices is a basic index depicting cohesiveness of a graph, and has been widely used in large-scale graph analytics. In this paper, we study the update of core numbers of vertices in dynamic graphs with edge insertions/deletions, which is known as the core maintenance problem. Di...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems Vol. 29; no. 11; pp. 2416 - 2428
Main Authors: Jin, Hai, Wang, Na, Yu, Dongxiao, Hua, Qiang-Sheng, Shi, Xuanhua, Xie, Xia
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
core number maintenance
Deletion
dynamic graph
Graph analysis
Graph theory
Graphs
Heuristic algorithms
Indexes
Maintenance
Maintenance engineering
Matching
parallel algorithm
Parallel algorithms
Scalability
Stability analysis
ISSN:1045-9219, 1558-2183
Online Access:Get full text
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Summary:The core number of vertices is a basic index depicting cohesiveness of a graph, and has been widely used in large-scale graph analytics. In this paper, we study the update of core numbers of vertices in dynamic graphs with edge insertions/deletions, which is known as the core maintenance problem. Different from previous approaches that just focus on the case of single-edge insertion/deletion and sequentially handle the edges when multiple edges are inserted/deleted, we investigate the parallelism in the core maintenance procedure. Specifically, we show that if the inserted/deleted edges constitute a matching, the core number update with respect to each inserted/deleted edge can be handled in parallel. Based on this key observation, we propose parallel algorithms for core maintenance in both cases of edge insertions and deletions. Extensive experiments are conducted to evaluate the efficiency, stability, parallelism and scalability of our algorithms on different types of real-world, synthetic graphs and temporal networks. Comparing with former approaches, our algorithms can improve the core maintenance efficiency significantly.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2018.2835441