Abstract:The existing frequent closed graph(FCG) mining methods under standalone mode can not process massive Internet datasets

by improving the Apriori algorithm

an iterative algorithm AMR(Apriori based on MapReduce) was proposed to mine FCGs of large scale dynamic networks based on Hadoop. First of all

the edge sets of dynamic networks were stored in the key-value table

and a serialized subgraph coding mechanism was designed to ensure the uniqueness of frequent subgraphs(FSG). Secondly

a communication mechanism was proposed to pass subgraph codes

and to ensure the accuracy of FCG

local supports in each partition were aggregated to a global one. Finally

FCGs were achieved by pruning the FSGs. AMR was used in the dynamic networks of both country and AS level Internet

and experimental results showed that FCG can accurately characterize the topology of backbone Internet

thus verifying the efficiency and effectiveness of AMR in mining FCG of large scale dynamic networks.