Abstract
Generation of social networks using Preferential Attachment (PA) mechanism is proposed in the Barabasi-Albert model. In this mechanism, new nodes are introduced to the network sequentially and they attach to the existing nodes preferentially where the preference can be based on the degree of the existing nodes. PA is a classical model with a natural intuition, great explanatory power and interesting mathematical properties. Some of these properties only appear in large-scale networks. However generation of such extra-large networks can be challenging due to memory limitations. In this paper, we investigate a distributed-memory approach for PA-based network generation which is scalable and which avoids low-level synchronization mechanisms thanks to utilizing a powerful programming model and proper programming constructs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Erdös, P., Rényi, A.: On the central limit theorem for samples from a finite population. Publ. Math. Inst. Hungar. Acad. Sci 4, 49–61 (1959)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 440–442 (1998)
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)
Tonelli, R., Concas, G., Locci, M.: Three efficient algorithms for implementing the preferential attachment mechanism in Yule-Simon stochastic process. WSEAS Trans. Inf. Sci. Appl. 7(2), 176–185 (2010)
Leskovec, J.: Dynamics of Large Networks. ProQuest, Ann Arbor (2008)
Bader, D., Madduri, K., et al.: Parallel algorithms for evaluating centrality indices in real-world networks. In: International Conference on Parallel Processing, ICPP 2006, pp. 539–550. IEEE (2006)
Johnsen, E.B., Hähnle, R., Schäfer, J., Schlatte, R., Steffen, M.: ABS: a core language for abstract behavioral specification. In: Aichernig, B.K., Boer, F.S., Bonsangue, M.M. (eds.) FMCO 2010. LNCS, vol. 6957, pp. 142–164. Springer, Heidelberg (2011). doi:10.1007/978-3-642-25271-6_8
Din, C.C., Bubel, R., Hähnle, R.: KeY-ABS: a deductive verification tool for the concurrent modelling language ABS. In: Felty, A.P., Middeldorp, A. (eds.) CADE 2015. LNCS, vol. 9195, pp. 517–526. Springer, Heidelberg (2015). doi:10.1007/978-3-319-21401-6_35
Albert, E., Arenas, P., Correas, J., Genaim, S., Gómez-Zamalloa, M., Puebla, G., Román-Díez, G.: Object-sensitive cost analysis for concurrent objects. Softw. Test. Verification Reliab. 25(3), 218–271 (2015)
Epstein, J., Black, A.P., Peyton-Jones, S.: Towards haskell in the cloud. In: ACM SIGPLAN Notices, vol. 46, pp. 118–129. ACM (2011)
Atwood, J., Ribeiro, B., Towsley, D.: Efficient network generation under general preferential attachment. Comput. Soc. Netw. 2(1), 1 (2015)
Batagelj, V., Brandes, U.: Efficient generation of large random networks. Phys. Rev. E 71(3), 036113 (2005)
Yoo, A., Henderson, K.: Parallel generation of massive scale-free graphs. arXiv preprint arXiv:1003.3684 (2010)
Lo, Y.C., Li, C.T., Lin, S.D.: Parallelizing preferential attachment models for generating large-scale social networks that cannot fit into memory. In: Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom), pp. 229–238. IEEE (2012)
Alam, M., Khan, M., Marathe, M.V.: Distributed-memory parallel algorithms for generating massive scale-free networks using preferential attachment model. In: Proceedings of SC13: International Conference for High Performance Computing, Networking, Storage and Analysis, p. 91. ACM (2013)
Şerbănescu, V., Azadbakht, K., de Boer, F.: A java-based distributed approach for generating large-scale social network graphs. In: Pop, F., Kołlodziej, J., Di Martino, B. (eds.) Resource Management for Big Data Platforms, pp. 401–417. Springer, Cham (2016)
Bezirgiannis, N., Boer, F.: ABS: a high-level modeling language for cloud-aware programming. In: Freivalds, R.M., Engels, G., Catania, B. (eds.) SOFSEM 2016. LNCS, vol. 9587, pp. 433–444. Springer, Heidelberg (2016). doi:10.1007/978-3-662-49192-8_35
Henrio, L., Rochas, J.: From modelling to systematic deployment of distributed active objects. In: Lluch Lafuente, A., Proença, J. (eds.) COORDINATION 2016. LNCS, vol. 9686, pp. 208–226. Springer, Heidelberg (2016). doi:10.1007/978-3-319-39519-7_13
Azadbakht, K., de Boer, F.S., Serbanescu, V.: Multi-threaded actors. arXiv preprint arXiv:1608.03322 (2016)
Azadbakht, K., Bezirgiannis, N., de Boer, F.S., Aliakbary, S.: A high-level and scalable approach for generating scale-free graphs using active objects. In: Proceedings of the 31st Annual ACM Symposium on Applied Computing, pp. 1244–1250. ACM (2016)
Kumar, R., Raghavan, P., Rajagopalan, S., Sivakumar, D., Tomkins, A., Upfal, E.: Stochastic models for the web graph. In: 2000 Proceedings of 41st Annual Symposium on Foundations of Computer Science, pp. 57–65. IEEE (2000)
Acknowledgments
Partly funded by the EU project FP7-612985 UpScale (http://www.upscale-project.eu) and the EU project FP7-610582 ENVISAGE (http://www.envisage-project.eu). This work was carried out on the Dutch national HPC cloud infrastructure, a service provided by the SURF Foundation (http://surf.nl).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Azadbakht, K., Bezirgiannis, N., de Boer, F.S. (2017). Distributed Network Generation Based on Preferential Attachment in ABS. In: Steffen, B., Baier, C., van den Brand, M., Eder, J., Hinchey, M., Margaria, T. (eds) SOFSEM 2017: Theory and Practice of Computer Science. SOFSEM 2017. Lecture Notes in Computer Science(), vol 10139. Springer, Cham. https://doi.org/10.1007/978-3-319-51963-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-51963-0_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51962-3
Online ISBN: 978-3-319-51963-0
eBook Packages: Computer ScienceComputer Science (R0)