A Multi-copy Join Optimization of Information Integration Systems Based on a Genetic Algorithm

In view of inevitable redundancies in local data sources in heterogeneous information integration systems, a multi-copy join optimization method (MuCoJo for short) based on a genetic algorithm is proposed. MuCoJo can choose appropriate redundant copies of the tables to participate a joint query and optimizes the join order of it. By using the redundant copies, MuCoJo enlarges the search space so that the concurrent executions of different local sources can be best used. Meanwhile, MuCoJo could take advantage of redundancies features in such systems and get faster joint query response time. Experimental results show the computational efficiency of the MuCoJo and its necessity in information integration system. Moreover, during the population initialization, controlling invalid solutions can reduce the search space effectively at the cost of initialization time consuming.