Abstract
The breadth of problems requiring graph analytics is growing rapidly. Diameter is one of the most important metrics of a graph. The diameter is important in both designing algorithms for graphs and understanding the nature and evolution of graphs. Besides, the real world graphs are always changing. So detecting diameter in both static and dynamic graphs is very important. We first present an algorithm to calculate the diameter of the static graphs. The main goal of this algorithm is to reduce the number of breadth-first searches required to determine diameter of the graph. In addition, another algorithm is presented for calculating the diameter of incremental graphs. This algorithm uses the proposed static algorithm in its body. Based on experimental results, our proposed algorithm can detect diameter of both static and incremental graphs faster than existing approaches. To the best of our knowledge, the second algorithm is the first one that is able to efficiently determine the diameter of disconnected graphs that will be connected over time by adding new vertices.








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References
Akiba, T., Iwata, Y., Kawata, Y.: An exact algorithm for diameters of large real directed graphs. In: Experimental Algorithms, pp. 56–67. Springer (2015)
Bawa, M., Cooper, B.F., Crespo, A., Daswani, N., Ganesan, P., Garcia-Molina, H., Kamvar, S., Marti, S., Schlosser, M., Sun, Q.: Peer-to-peer research at Stanford. ACM SIGMOD Rec. 32(3), 23–28 (2003)
Chechik, S., Larkin, D.H., Roditty, L., Schoenebeck, G., Tarjan, R.E., Williams, V.: Better approximation algorithms for the graph diameter. In: Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1041–1052. SIAM (2014)
Chung, F., Lu, L.: The diameter of sparse random graphs. Adv. Appl. Math. 26(4), 257–279 (2001)
Crescenzi, P., Grossi, R., Habib, M., Lanzi, L., Marino, A.: On computing the diameter of real-world undirected graphs. Theor. Comput. Sci. 514, 84–95 (2013)
Crescenzi, P., Grossi, R., Imbrenda, C., Lanzi, L., Marino, A.: Finding the diameter in real-world graphs. In: Algorithms--ESA 2010, pp. 302–313. Springer (2010)
Crescenzi, P., Grossi, R., Lanzi, L., Marino, A.: On computing the diameter of real-world directed (weighted) graphs. In: Experimental Algorithms, pp. 99–110. Springer (2012)
Fujiwara, Y., Onizuka, M., Kitsuregawa, M.: Real-time diameter monitoring for time-evolving graphs. In: Database Systems for Advanced Applications, pp. 311–325. Springer (2011)
Jure, L., Andrej, K.: SNAP datasets: Stanford large network dataset collection. [Online]. Available: http://snap.stanford.edu/data (2014)
Kumar, A., Merugu, S., Xu, J.J., Zegura, E.W., Yu, X.: Ulysses: a robust, low-diameter, low-latency peer-to-peer network. Eur. Trans. Telecommun. 15(6), 571–587 (2004)
Malewicz, G., Austern, M.H., Bik, A.J.C., Dehnert, J.C., Horn, I., Leiser, N., Czajkowski, G.: Pregel: a system for large-scale graph processing. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, pp. 135–146. ACM (2010)
Masoud, S., Hassan, N., Mostafa, H.: ExPregel: a new computational model for large-scale graph processing. Concurr. Comput. 27(17), 4954–4969 (2015)
Newman, M.E.: The structure and function of complex networks. SIAM Rev. 45(2), 167–256 (2003)
Reka, A., Hawoong, J., Albert-Laszlo, B.: Internet: Diameter of the world-wide web. Nature 401(6749), 130–131 (1999)
Roditty, L., Vassilevska Williams, V.: Fast approximation algorithms for the diameter and radius of sparse graphs. In: Proceedings of the Forty-Fifth Annual ACM Symposium on Theory of Computing, pp. 515–524. ACM (2013)
Shudong, J., Azer, B.: Small-world characteristics of internet topologies and implications on multicast scaling. Comput. Netw. 50(5), 648–666 (2006)
Takes, F.W., Kosters, W.A.: Determining the diameter of small world networks. In: Proceedings of the 20th ACM international conference on Information and knowledge management, pp. 1191–1196. ACM (2011)
Walshaw, C.: The university of greenwich gaph partitioning archive. [Online]. Available: http://staffweb.cms.gre.ac.uk/~c.walshaw/partition/ ( 2000). Accessed 2015
Wasserman, S.: Social network analysis Methods and applications. Cambridge University Press (1994)
Yan, D., Cheng, J., Lu, Y., Ng, W.: Blogel: A block-centric framework for distributed computation on real-world graphs. Proc. VLDB Endow. 7(14), 1981–1992 (2014)
Yuster, R.: Computing the diameter polynomially faster than APSP. arXiv preprint arXiv:1011.6181 (2010)
Zwick, U.: Exact and approximate distances in graphs—a survey. In: Algorithms—ESA 2001, pp. 33–48. Springer (2001)
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Sagharichian, M., Alipour Langouri, M. & Naderi, H. A fast method to exactly calculate the diameter of incremental disconnected graphs. World Wide Web 20, 399–416 (2017). https://doi.org/10.1007/s11280-016-0394-0
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DOI: https://doi.org/10.1007/s11280-016-0394-0