Workflow Scheduling on distributed systems

Growing evidence shows that in obtaining high performance, a well-managed time-constrained workflow scheduling is needed. Efficient workflow scheduling is critical for achieving high performance especially in heterogeneous computing system. However, it is a great challenge to improve performance and to optimize several objectives simultaneously. We propose a workflow scheduling algorithm that minimizes the makespan of the workflow application modeled by a Directed Acyclic Graph (DAG). The new proposed scheduling algorithm is named Multi Dependency Joint (MDJ) Algorithm. The performance of MDJ is compared with existing algorithms such as, Highest Level First with Estimated Time (HLFET), Modified Critical Path (MCP) and Earliest Time First (ETF). As a result, the experiments show that our proposed MDJ algorithm outperforms HLEFT, MCP, and EFT with a 7% lower overall completion time.