One of the distinct characteristics of computing platforms shared by multiple users such as a computational grid is heterogeneity on each computer and/or among computers. Temporal heterogeneity refers to variation, along the time dimension, of computing power (or communication bandwidth) available for a task on a computer, and spatial heterogeneity represents the variation among computers. In minimizing the average parallel execution time of a target task on a spatially heterogeneous computing system, it is not optimal to distribute the target task linearly proportional to the average computing powers available on computers. In this study, based on a theoretical model of heterogeneous computing environment, an approach to load balancing for minimizing the average parallel execution time of a target task is discussed. The approach of which validity has been verified through simulation considers temporal and spatial heterogeneities in addition to the average computing power on each computer.