Process migration is essential for runtime load balancing. In Grid and shared networked environments, load imbalance is not only caused by the dynamic nature of underlying applications, but also by the fluctuation of resource availability. In a shared environment, tasks need to be rescheduled frequently to adapt the variation of resources availability. Unlike conventional task scheduling, dynamic rescheduling has to consider process migration costs in its formulation. In this study, we first model the migration cost and introduce an effective method to predict the cost. We then introduce a dynamic scheduling mechanism that considers migration cost as well as other conventional influential factors for performance optimization in a shared, heterogeneous environment. Finally we present experimental testing to verify the analytical results. Experimental results show that the proposed dynamic scheduling system is feasible and improves the system performance considerably.