On dynamic succinct graph representations

11/08/2019
by   Miguel E. Coimbra, et al.
0

We address the problem of representing dynamic graphs using k^2-trees. The k^2-tree data structure is one of the succinct data structures proposed for representing static graphs, and binary relations in general. It relies on compact representations of bit vectors. Hence, by relying on compact representations of dynamic bit vectors, we can also represent dynamic graphs. In this paper we follow instead the ideas by Munro et al., and we present an alternative implementation for representing dynamic graphs using k^2-trees. Our experimental results show that this new implementation is competitive in practice.

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References

  • [1] Paolo Boldi and Sebastiano Vigna, “The webgraph framework I: compression techniques,” in World Wide Web Conference (WWW), 2004, pp. 595–602.
  • [2] Nieves R. Brisaboa, Susana Ladra, and Gonzalo Navarro, “Compact representation of web graphs with extended functionality,” Information Systems, vol. 39, pp. 152–174, 2014.
  • [3] Nieves R. Brisaboa, Ana Cerdeira-Pena, Guillermo de Bernardo, and Gonzalo Navarro, “Compressed representation of dynamic binary relations with applications,” Information Systems, vol. 69, pp. 106–123, 2017.
  • [4] J. Ian Munro, Yakov Nekrich, and Jeffrey Scott Vitter, “Dynamic data structures for document collections and graphs,” in ACM Symposium on Principles of Database Systems (PODS), 2015, pp. 277–289.
  • [5] Gonzalo Navarro, Compact data structures: A practical approach, Cambridge University Press, 2016.
  • [6] Carlos Quijada-Fuentes, Miguel R. Penabad, Susana Ladra, and Gilberto Gutiérrez, “Set operations over compressed binary relations,” Information Systems, vol. 80, pp. 76–90, 2019.
  • [7] Diego Arroyuelo, Guillermo de Bernardo, Travis Gagie, and Gonzalo Navarro, “Faster dynamic compressed d-ary relations,” in String Processing and Information Retrieval (SPIRE), 2019, pp. 419–433.
  • [8] Paolo Boldi and Sebastiano Vigna, “The WebGraph framework I: Compression techniques,” in World Wide Web Conference (WWW), 2004, pp. 595–601.
  • [9] Paolo Boldi, Marco Rosa, Massimo Santini, and Sebastiano Vigna, “Layered label propagation: A multiresolution coordinate-free ordering for compressing social networks,” in World Wide Web Conference (WWW), 2011, pp. 587–596.
  • [10] Fan Chung, Linyuan Lu, T Gregory Dewey, and David J Galas, “Duplication models for biological networks,” Journal of Computational Biology, vol. 10, no. 5, pp. 677–687, 2003.
  • [11] Ashish Bhan, David J Galas, and T Gregory Dewey, “A duplication growth model of gene expression networks,” Bioinformatics, vol. 18, no. 11, pp. 1486–1493, 2002.