Skip to main navigation Skip to search Skip to main content

Pool Compression for Undirected Graphs

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We present a new graph compression scheme that intrinsically exploits the similarity and locality of references in a graph by first ordering the nodes and then merging the contiguous adjacency lists of the graph into blocks to create a pool of nodes. The nodes in the adjacency lists of the graph are encoded by their position in the pool. This simple yet powerful scheme achieves compression ratios better than the previous methods for many datasets tested in this paper and, on average, surpasses all the previous methods. The scheme also provides an easy and efficient access to neighbor queries, e.g., finding the neighbors of a node, and reachability queries, e.g., finding if node u is reachable from node v. We test our scheme on publicly available graphs of different sizes and show a significant improvement in the compression ratio and query access time compared to the previous approaches.

Original languageEnglish
Pages (from-to)58904-58912
Number of pages9
JournalIEEE Access
Volume10
DOIs
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Elias-Gamma encoding
  • Graph compression
  • merging adjacency lists
  • node ordering

Fingerprint

Dive into the research topics of 'Pool Compression for Undirected Graphs'. Together they form a unique fingerprint.

Cite this