A high-level and scalable approach for generating scale-free graphs using active objects

Azadbakht, Keyvan; Bezirgiannis, Nikolaos; de Boer, Frank; Aliakbary, Sadegh

doi:10.1145/2851613.2851722

K. Azadbakht (Keyvan), N. Bezirgiannis (Nikolaos), F.S. de Boer (Frank) and Aliakbary, S. (Sadegh)

2016-04-04

A high-level and scalable approach for generating scale-free graphs using active objects

Presented at the Annual ACM Symposium on Applied Computing (April 2016), Pisa, Italy

The Barabasi-Albert model (BA) is designed to generate scale-free networks using the preferential attachment mechanism. In the preferential attachment (PA) model, new nodes are sequentially introduced to the network and they attach preferentially to existing nodes. PA is a classical model with a natural intuition, great explanatory power and a simple mechanism. Therefore, PA is widely-used for network generation. However the sequential mechanism used in the PA model makes it an inefficient algorithm. The existing parallel approaches, on the other hand, suffer from either changing the original model or explicit complex low-level synchronization mechanisms. In this paper we investigate a high-level Actor-based model of the parallel algorithm of network generation and its scalable multicore implementation in Haskell.

Additional Metadata
Persistent URL	doi.org/10.1145/2851613.2851722
Conference	Annual ACM Symposium on Applied Computing
Organisation	Computer Security
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Azadbakht, K., Bezirgiannis, N., de Boer, F., & Aliakbary, S. (Sadegh). (2016). A high-level and scalable approach for generating scale-free graphs using active objects. Presented at the ACM Symposium on Applied Computing. doi:10.1145/2851613.2851722