A vertex-centric graph simulation algorithm for large graphs

Graph simulation as a well studied model of graph pattern matching problem, has been adopted to reduce the complexity and meet the need of novel applications such as mining potential associations between users in online social networks. In recent years, graph processing frameworks such as Pregel bring in a vertex-centric, Bulk Synchronous Parallel (BSP) programming model for processing massive data graphs and achieve encouraging results. However, developing efficient vertex-centric algorithms for graph simulation model is very challenging, because this problem does not naturally align with a vertex-centric programming model. This paper presents novel distributed algorithms based on the vertex-centric programming model for graph simulation. At the same time, considering the enormous cost of the message passing and the algorithm complexity of the pattern matching in the processing of the massive data graph, the part of message passing in the algorithm is optimized to reduce the communication cost. We experimentally verify the effectiveness and efficiency of these algorithms, using real-life massive data graph.