Skip to main content

On Some Combinatorial Properties of Random Intersection Graphs

  • Chapter
  • First Online:
Algorithms, Probability, Networks, and Games

Abstract

In this paper, we consider a simple, yet general family of random graph models, namely Random Intersection Graphs (RIGs), which are motivated by applications in secure sensor networks, social networks and many more. In such models there is a universe \(\mathcal{M}\) of labels and each one of n vertices selects a random subset of \(\mathcal{M}\). Two vertices are connected if and only if their corresponding subsets of labels intersect. In particular, we briefly review the state of the art and we present key results from our research on the field, that highlight and take advantage of the intricacies and special structure of random intersection graphs. Finally, we present in more detail a particular result from our research, which concerns maximum cliques in the uniform random intersection graphs model (in which every vertex selects each label independently with some probability p), namely the Single Label Clique Theorem.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    A perfect graph is a graph in which the chromatic number of every induced subgraph equals the size of the largest clique of that subgraph. Consequently, the clique number of a perfect graph is equal to its chromatic number.

References

  1. Aldous, D., Fill, J.A.: Reversible Markov Chains and Random Walks on Graphs. Unfinished monograph, recompiled (2014). Accessed on http://www.stat.berkeley.edu/~aldous/RWG/book.html

  2. Behrisch, M., Taraz, A., Ueckerdt, M.: Coloring random intersection graphs and complex networks. SIAM J. Discrete Math. 23, 288–299 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  3. Blackburn, S., Stinson, D., Upadhyay, J.: On the complexity of the herding attack and some related attacks on hash functions. Des. Codes Crypt. 64(1–2), 171–193 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  4. Bloznelis, M., Jaworski, J., Rybarczyk, K.: Component evolution in a secure wireless sensor network. Networks 53, 19–26 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  5. Cooper, C., Frieze, A.: The cover time of sparse random graphs. Random Struct. Algorithms 30, 1–16 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  6. Deijfen, M., Kets, W.: Random intersection graphs with tunable degree distribution and clustering. Probab. Eng. Inform. Sci. 23, 661–674 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  7. Chan, H., Perrig, A., Song, D.: Random key predistribution schemes for sensor networks. In: Proceedings of the IEEE Symposium on Security and Privacy (2003)

    Google Scholar 

  8. Efthymiou, C., Spirakis, P.G.: Sharp thresholds for Hamiltonicity in random intersection graphs. Theor. Comput. Sci. 411(40–42), 3714–3730 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  9. Fill, J.A., Sheinerman, E.R., Singer-Cohen, K.B.: Random intersection graphs when \(m = \omega (n)\): an equivalence theorem relating the evolution of the \(G(n, m, p)\) and \(G(n, p)\) models. Random Struct. Algorithms 16(2), 156–176 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  10. Frieze, A.: On the Independence Number of Random Graphs. Disc. Math. 81, 171–175 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  11. Godehardt, E., Jaworski, J.: Two models of random intersection graphs for classification. In: Opitz, O., Schwaiger, M. (eds.) Exploratory Data Analysis in Empirical Research. Studies in Classification, Data Analysis, and Knowledge Organization, pp. 67–82. Springer, Heidelberg (2002)

    Google Scholar 

  12. Karoński, M., Sheinerman, E.R., Singer-Cohen, K.B.: On random intersection graphs: the subgraph problem. Comb. Probab. Comput. j. 8, 131–159 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  13. Łuczak, T.: The chromatic number of random graphs. Combinatorica 11(1), 45–54 (2005)

    MathSciNet  MATH  Google Scholar 

  14. Nikoletseas, S., Raptopoulos, C., Spirakis, P.G.: Colouring non-sparse random intersection graphs. In: Královič, R., Niwiński, D. (eds.) MFCS 2009. LNCS, vol. 5734, pp. 600–611. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  15. Nikoletseas, S., Raptopoulos, C., Spirakis, P.G.: Expander properties and the cover time of random intersection graphs. Theor. Comput. Sci. 410(50), 5261–5272 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  16. Nikoletseas, S., Raptopoulos, C., Spirakis, P.G.: Large independent sets in general random intersection graphs. Theor. Comput. Sci. 406, 215–224 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  17. Nikoletseas, S., Raptopoulos, C., Spirakis, P.G.: Maximum cliques in graphs with small intersection number and random intersection graphs. In: Rovan, B., Sassone, V., Widmayer, P. (eds.) MFCS 2012. LNCS, vol. 7464, pp. 728–739. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  18. Nikoletseas, S., Raptopoulos, C., Spirakis, P.G.: On the independence number and hamiltonicity of uniform random intersection graphs. Theor. Comput. Sci. 412(48), 6750–6760 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  19. Molloy, M., Reed, B.: Graph Colouring and the Probabilistic Method. Springer, Heidelberg (2002)

    Book  MATH  Google Scholar 

  20. Raptopoulos, C., Spirakis, P.G.: Simple and efficient greedy algorithms for hamilton cycles in random intersection graphs. In: Deng, X., Du, D.-Z. (eds.) ISAAC 2005. LNCS, vol. 3827, pp. 493–504. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  21. Rybarczyk, K.: Equivalence of a random intersection graph and \(G(n, p)\). Random Struct. Algorithms 38(1–2), 205–234 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  22. Shang, Y.: On the isolated vertices and connectivity in random intersection graphs. Int. J. Comb. 2011. Article ID 872703 (2011). doi:10.1155/2011/872703

  23. Singer-Cohen, K.B.: Random Intersection Graphs. Ph.D. thesis, John Hopkins University (1995)

    Google Scholar 

  24. Stark, D.: The vertex degree distribution of random intersection graphs. Random Struct. Algorithms 24(3), 249–258 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  25. Yağan, O., Makowski, A.M.: Zero-one laws for connectivity in random key graphs. IEEE Trans. Inf. Theor. 58(5), 2983–2999 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  26. Zhao, J., Yağan, O., Gligor, V.: On \(k\)-connectivity and minimum vertex degree in random \(s\)-intersection graphs. Arxiv e-prints (2014). Accessed on http://arxiv.org/pdf/1409.6021v3.pdf

  27. Zhao, J., Yağan, O., Gligor, V.: On the strengths of connectivity and robustness in general random intersection graphs. In: Proceedings of the IEEE Conference on Decision and Control (CDC), December 2014

    Google Scholar 

Download references

Acknowledgment

This paper is devoted to our mentor Paul Spirakis, on the occasion of his 60th birthday. It was Paul who pointed out to us the very interesting model of Random Intersection Graphs and inspired us to work, as a team, on its exploration.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christoforos L. Raptopoulos .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Nikoletseas, S.E., Raptopoulos, C.L. (2015). On Some Combinatorial Properties of Random Intersection Graphs. In: Zaroliagis, C., Pantziou, G., Kontogiannis, S. (eds) Algorithms, Probability, Networks, and Games. Lecture Notes in Computer Science(), vol 9295. Springer, Cham. https://doi.org/10.1007/978-3-319-24024-4_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-24024-4_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24023-7

  • Online ISBN: 978-3-319-24024-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics