Performance Analysis of Grid DAG Scheduling Algorithms using MONARC Simulation Tool

This paper presents a solution to analyze the performance of grid scheduling algorithms for tasks with dependencies. Finding the optimal procedures for DAG scheduling in Grid systems is important due to the latest computing necessities: large scale distributed computing and complex applications for different research areas. We propose a solution to evaluate DAG scheduling algorithms using simulation, an approach suitable to evaluate different scheduling algorithms using various task dependencies and considering a wide range of Grid system architectures. Our proposed solution is based on MONARC, a generic simulation framework designed for modeling large scale distributed systems. We present our research results in extending the simulation platform to accommodate various DAG scheduling procedures and, as a case study, we present a critical analysis of four well known DAG scheduling strategies: CCF (Cluster ready Children First), ETF (Earliest Time First), HLFET (Highest Level First with Estimated Times) and Hybrid Remapper. The obtained results show that the proposed solution is a very good instrument for evaluating performance in case of a wide range of DAG scheduling algorithms.