Introducing an Efficient Method for Scheduling Independent Tasks in Grid Environment using Meta-Heuristic Algorithms

Masoud Shirzadi, Mortaza Zolfpour-Arokhlo, Majid Sina


Since the dynamicity and inhomogeneity of resources complicates scheduling, it is not possible to use accurate scheduling algorithms. Therefore, many studies focus on heuristic algorithms like the artificial bee colony algorithm. Since, the artificial bee colony algorithm searches the problem space locally and has a poor performance in global search; global search algorithms like genetic algorithms should also be used to overcome this drawback. This study proposes a scheduling algorithm, which is combination of the genetic and artificial bee colony algorithms for the independent scheduling problem in a computing grid. This study aims to reduce the maximum total scheduling time. Simulation results indicate that the proposed algorithm reduces the maximum execution time (makespan) by 10% in comparison to the compared methods.


computing grid; independent task scheduling; genetic algorithm; artificial bee colony algorithm

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