A high-level and scalable approach for generating scale-free graphs using active objects
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.
|Conference||Annual ACM Symposium on Applied Computing|
Azadbakht, K, Bezirgiannis, N, de Boer, F.S, & 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