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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 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
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
Behrisch, M., Taraz, A., Ueckerdt, M.: Coloring random intersection graphs and complex networks. SIAM J. Discrete Math. 23, 288–299 (2008)
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)
Bloznelis, M., Jaworski, J., Rybarczyk, K.: Component evolution in a secure wireless sensor network. Networks 53, 19–26 (2009)
Cooper, C., Frieze, A.: The cover time of sparse random graphs. Random Struct. Algorithms 30, 1–16 (2007)
Deijfen, M., Kets, W.: Random intersection graphs with tunable degree distribution and clustering. Probab. Eng. Inform. Sci. 23, 661–674 (2009)
Chan, H., Perrig, A., Song, D.: Random key predistribution schemes for sensor networks. In: Proceedings of the IEEE Symposium on Security and Privacy (2003)
Efthymiou, C., Spirakis, P.G.: Sharp thresholds for Hamiltonicity in random intersection graphs. Theor. Comput. Sci. 411(40–42), 3714–3730 (2010)
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)
Frieze, A.: On the Independence Number of Random Graphs. Disc. Math. 81, 171–175 (1990)
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)
Karoński, M., Sheinerman, E.R., Singer-Cohen, K.B.: On random intersection graphs: the subgraph problem. Comb. Probab. Comput. j. 8, 131–159 (1999)
Łuczak, T.: The chromatic number of random graphs. Combinatorica 11(1), 45–54 (2005)
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)
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)
Nikoletseas, S., Raptopoulos, C., Spirakis, P.G.: Large independent sets in general random intersection graphs. Theor. Comput. Sci. 406, 215–224 (2008)
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)
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)
Molloy, M., Reed, B.: Graph Colouring and the Probabilistic Method. Springer, Heidelberg (2002)
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)
Rybarczyk, K.: Equivalence of a random intersection graph and \(G(n, p)\). Random Struct. Algorithms 38(1–2), 205–234 (2011)
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
Singer-Cohen, K.B.: Random Intersection Graphs. Ph.D. thesis, John Hopkins University (1995)
Stark, D.: The vertex degree distribution of random intersection graphs. Random Struct. Algorithms 24(3), 249–258 (2004)
Yağan, O., Makowski, A.M.: Zero-one laws for connectivity in random key graphs. IEEE Trans. Inf. Theor. 58(5), 2983–2999 (2012)
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
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
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
Corresponding author
Editor information
Editors and Affiliations
Rights 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)