MapReduce-based large-scale online social network worm simulation

Abstract

This paper provides an approach for simulating the propagation of online social network worms, based on MapReduce, a key component of the cloud computing. In order to improve the simulation accuracy, the approach describes the phases of the worms' propagation with OSN directed graph, in which each node owns its tunable attributes. Then, the phases are simulated by different map-functions and reduce-functions, which will finally run in the cloud environment. The experimental results on the real large network datasets show that the simulating approach is scalable and helpful in the research of online social network worms. © 2013 ISCAS.