A Segmented Approach for DAG Scheduling in Heterogeneous Environment

Task scheduling optimization is crucial in order to achieve maximum advantage out of available resources having diverse characteristics. In heterogeneous environment scheduling set of dependent tasks involve two dimensional considerations. Tasks are supposed to be assigned to best suited machines while avoiding the extra overhead of communication cost which should ultimately enhance the performance mostly in terms of minimizing the completion time of a job. Extensive research work has been done addressing the same problem domain and number of well-known heuristics has been proposed. In this paper a new heuristic is proposed which assign priorities to the set of dependent tasks based on three different parameters which are average computation cost, average communication cost and mean of both. A segmented approach is introduced which schedules tasks based on nature set of tasks in terms of computation cost and there precedence constraints. The experimental results show the better performance of proposed heuristic.