Abstract
Halldórsson, Sun, Szegedy, and Wang (ICALP 2012) [16] investigated the space complexity of the following problem CLIQUE-GAP(r, s): given a graph stream G, distinguish whether \(\omega (G) \ge r\) or \(\omega (G) \le s\), where \(\omega (G)\) is the clique-number of G. In particular, they give matching upper and lower bounds for CLIQUE-GAP(r, s) for any r and \(s =c\log (n)\), for some constant c. The space complexity of the CLIQUE-GAP problem for smaller values of s is left as an open question. In this paper, we answer this open question. Specifically, for \(s=\tilde{O}(\log (n))\) and for any \(r>s\), we prove that the space complexity of CLIQUE-GAP problem is \(\tilde{\varTheta }(\frac{ms^2}{r^2})\). Our lower bound is based on a new connection between graph decomposition theory (Chung, Erdös, and Spencer [11], and Chung [10]) and the multi-party set disjointness problem in communication complexity.
V. Braverman—This material is based upon work supported in part by the National Science Foundation under Grant No. 1447639, by the Google Faculty Award and by DARPA grant N660001-1-2-4014. Its contents are solely the responsibility of the authors and do not represent the official view of DARPA or the Department of Defense.
Z. Liu—This work is supported in part by DARPA grant N660001-1-2-4014.
N.V. Vinodchandran—Research supported in part by National Science Foundation grant CCF-1422668.
L.F. Yang—This work is supported in part by NSF grant No. 1447639.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
In this and following theorems, the constants we choose are only for demonstrative convenience.
- 2.
In this and following theorems, the constants we choose are only for demonstrative convenience.
- 3.
Note that some papers define the decomposition on connected graph. We here use a more general statement.
References
Ahn, K.J., Guha, S.: Graph sparsification in the semi-streaming model. In: Albers, S., Marchetti-Spaccamela, A., Matias, Y., Nikoletseas, S., Thomas, W. (eds.) ICALP 2009, Part II. LNCS, vol. 5556, pp. 328–338. Springer, Heidelberg (2009)
Alon, N., Krivelevich, M., Sudakov, B.: Finding a large hidden clique in a random graph. In: Proceedings of the Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 594–598. ACM/SIAM (1998). http://dl.acm.org/citation.cfm?id=314613.315014
Alon, N., Matias, Y., Szegedy, M.: The space complexity of approximating the frequency moments. In: Proceedings of the Twenty-eighth Annual ACM Symposium on Theory of Computing. pp. 20–29. ACM (1996)
Bar-Yossef, Z., Kumar, R., Sivakumar, D.: Reductions in streaming algorithms, with an application to counting triangles in graphs. In: Proceedings of the Thirteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 623–632. SODA, Society for Industrial and Applied Mathematics (2002)
Buriol, L.S., Frahling, G., Leonardi, S., Marchetti-Spaccamela, A., Sohler, C.: Computing clustering coefficients in data streams. In: European Conference on Complex Systems (ECCS) (2006)
Buriol, L.S., Frahling, G., Leonardi, S., Marchetti-Spaccamela, A., Sohler, C.: Counting triangles in data streams. In: Proceedings of the Twenty-fifth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS), pp. 253–262. ACM (2006)
Buriol, L.S., Frahling, G., Leonardi, S., Sohler, C.: Estimating clustering indexes in data streams. In: Arge, L., Hoffmann, M., Welzl, E. (eds.) ESA 2007. LNCS, vol. 4698, pp. 618–632. Springer, Heidelberg (2007)
Buriol, L.S., Frahling, G., Leonardi, S., Spaccamela, A.M., Sohler, C.: Counting graph minors in data streams. Technical report, DELIS - Dynamically Evolving, Large-Scale Information Systems (2005)
Chakrabarti, A., Khot, S., Sun, X.: Near-optimal lower bounds on the multi-party communication complexity of set disjointness. In: IEEE Conference on Computational Complexity, pp. 107–117. IEEE Computer Society (2003)
Chung, F.: On the decomposition of graphs. SIAM J. Algebraic Discrete Methods 2(1), 1–12 (1981)
Chung, F., Erdős, P., Spencer, J.: On the decomposition of graphs into complete bipartite subgraphs. In: Erdős, P., Alpár, L., Halász, H., SárkÖz, A. (eds.) Studies in Pure Mathematics, pp. 95–101. Birkhäuser, Basel (1983)
Cormode, G., Jowhari, H.: A second look at counting triangles in graph streams. Theoret. Comput. Sci. 552, 44–51 (2014)
Demetrescu, C., Finocchi, I., Ribichini, A.: Trading off space for passes in graph streaming problems. In: Proceedings of ACM-SIAM Symposium on Discrete Algorithms. pp. 714–723. ACM (2006)
Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52, 1289–1306 (2006)
Goel, A., Kapralov, M., Khanna, S.: On the communication and streaming complexity of maximum bipartite matching. In: Proceedings of the Twenty-third Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 468–485. SIAM (2012)
Halldórsson, M.M., Sun, X., Szegedy, M., Wang, C.: Streaming and communication complexity of clique approximation. In: Czumaj, A., Mehlhorn, K., Pitts, A., Wattenhofer, R. (eds.) ICALP 2012, Part I. LNCS, vol. 7391, pp. 449–460. Springer, Heidelberg (2012)
Jha, M., Seshadhri, C., Pinar, A.: When a graph is not so simple: Counting triangles in multigraph streams. CoRR abs/1310.7665 (2013). http://arxiv.org/abs/1310.7665
Jowhari, H., Ghodsi, M.: New Streaming algorithms for counting triangles in graphs. In: Wang, L. (ed.) COCOON 2005. LNCS, vol. 3595, pp. 710–716. Springer, Heidelberg (2005)
Kapralov, M., Khanna, S., Sudan, M.: Streaming lower bounds for approximating MAX-CUT. CoRR abs/1409.2138 (2014). http://arxiv.org/abs/1409.2138
Kutzkov, K., Pagh, R.: On the streaming complexity of computing local clustering coefficients. In: Proceedings of the Sixth ACM International Conference on Web Search and Data Mining (WSDM), pp. 677–686. ACM (2013)
Manjunath, M., Mehlhorn, K., Panagiotou, K., Sun, H.: Approximate counting of cycles in streams. In: Demetrescu, C., Halldórsson, M.M. (eds.) ESA 2011. LNCS, vol. 6942, pp. 677–688. Springer, Heidelberg (2011)
McGregor, A.: Graph stream algorithms: a survey. SIGMOD Rec. 43(1), 9–20 (2014). http://doi.acm.org/10.1145/2627692.2627694
Pavan, A., Tangwongsan, K., Tirthapura, S., Wu, K.L.: Counting and sampling triangles from a graph stream. Proc. VLDB Endowment 6(14), 1870–1881 (2013)
Ugander, J., Karrer, B., Backstrom, L., Marlow, C.: The anatomy of the facebook social graph. CoRR abs/1111.4503 (2011). http://arxiv.org/abs/1111.4503
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Braverman, V., Liu, Z., Singh, T., Vinodchandran, N.V., Yang, L.F. (2015). New Bounds for the CLIQUE-GAP Problem Using Graph Decomposition Theory. In: Italiano, G., Pighizzini, G., Sannella, D. (eds) Mathematical Foundations of Computer Science 2015. MFCS 2015. Lecture Notes in Computer Science(), vol 9235. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48054-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-662-48054-0_13
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-48053-3
Online ISBN: 978-3-662-48054-0
eBook Packages: Computer ScienceComputer Science (R0)