A Hybrid Time Management Approach for Social Network Simulation

Parallel Simulation Technique plays a more and more important role in researching large scale social networks.Synchronization is the crucial factor to affect the parallel simulation performance.Nowadays,it is an important topic of synchronization study to exploit application characteristics so as to develop an effective synchronization algorithm.Due to the larger differences of individual behaviors in the large scale social networks,the conservative approach may become limited by sensitivity to lookahead;due to the complex individual interaction,the optimistic approach appears to be prone to cascading rollbacks.In this paper,we propose a hybrid time management approach where a logic process can autonomously choose to be optimistic or conservative,and optimize the selection by utilizing the community detection.The experimental results demonstrate the efficiency of our methodology.