As the number of nodes in high performance computing (HPC) systems increases, collective I/O becomes an important issue and I/O aggregators are the key factors in improving the performance of collective I/O. When an HPC system uses non-exclusive scheduling, a different number of CPU cores per node can be assigned for MPI jobs; thus, I/O aggregators experience a disparity in their workloads and communication costs. Because the communication behaviors are influenced by the sequence of the I/O aggregators and by the number of CPU cores in neighbor nodes, changing the order of the nodes affects the communication costs in collective I/O. There are few studies, however, that seek to incorporate steps to adequately determine the node sequence. In this study, it was found that an inappropriate order of nodes results in an increase in the collective I/O communication costs. In order to address this problem, we propose the use of specific heuristic methods to regulate the node sequence. We also develop a prediction function in order to estimate the MPI-IO performance when using the proposed heuristic functions. The performance measurements indicated that the proposed scheme achieved its goal of preventing the performance degradation of the collective I/O process. For instance, in a multi-core cluster system with the Lustre file system, the read bandwidth of MPI-Tile-IO was improved by 7.61% to 17.21% and the write bandwidth of the benchmark was also increased by 17.05% to 26.49%.