An optimal candidate selection model for self-acting load balancing of parallel file system

The load imbalance among the I/O servers of parallel file systems is an emerging challenge to effectively utilise the high-end computing system. However, most contemporary parallel file systems lack the ability to handle the load imbalance among the I/O servers. In order to address this problem, a self-acting load balancing strategy is proposed in this paper. The self-acting load balancing is based on two novel components: a statistic model which measures the relationship between the response time and the load of I/O server and an optimal candidate selection model for the dynamic file migration. The experimental results show that the parallel file system with the proposed load balancing scheme can improve the performance of parallel I/O.