Optimal task scheduling algorithm for non-preemptive processing system

We present a new task scheduling problem in which tasks have a non-preemptive processing time and a rigid deadline for completion. For the solution to the problem, we propose a mathematical formulation and a two-phased algorithm to minimize total transition cost between tasks. In the first phase, the algorithm generates feasible allocations satisfying the deadline constraint using dynamic programming, and then in the second phase it finds optimal solution through a matching procedure. Performance evaluation shows that the proposed algorithm has good execution time efficiency for parallel and distributed systems composed of large quantity of processors.