An adaptive scheduling algorithm for molecule docking design on grid

Grid provides a promising platform for the efficient execution of drug molecular docking design. Scheduling such applications is challenging for the heterogeneity, autonomy, and dynamic adaptability of grid resources. Assuming resource owners have a preemptive priority, we propose an adaptive algorithm of jobs scheduling based on time balancing strategy, which solves parallel molecular docking task by using the idle resources in the Grid. A mathematical model is developed to predict performance, which also considers systems with heterogeneous machine utilization and heterogeneous service distribution. According to the time balancing policy, ligands are partitioned into several subtasks and scheduled. The expected value of molecular docking completion time is predicted with performance model. To get better parallel computing performance, an optimal subset of heterogeneous resources with the shortest parallel executing time of tasks can be selected with the algorithm.