Improving scheduling of tasks using Delay Adjust in a Heterogeneous environment

Optimal scheduling of parallel tasks with some precedence is critical for achieving high performance in heterogeneous computing system. The application scheduling is known to be NP-complete in general cases. The complexity of the problem increase when task scheduling is to be done in a heterogeneous environment, where the processors in the network may not be identical and take different amounts of time to execute the same task. This paper presents a task scheduling algorithm for the tasks run on the network of Heterogeneous systems and represented by Directed Acyclic Graphs (DAGs). The algorithm first assigns the tasks on processors and orders their execution so that task precedence requirements are satisfied. Then it shortens overall completion time by inserting the task into the slack that is created by delaying some tasks without exceeding the current completion time. The performance of the algorithm is illustrated by comparing the scheduling length ratio, frequency of best results with the existing effectively scheduling algorithms, Heterogeneous Earliest Finish Time and Iterative List Scheduling algorithm.