Rule-based scheduling algorithms have been
widely used on many cloud computing systems because they are simple and easy to
implement. However, there is plenty of room to improve the performance of these
algorithms, especially by using heuristic scheduling. As such, this paper
presents a novel heuristic scheduling algorithm, called hyper-heuristic
scheduling algorithm (HHSA), to find better scheduling solutions for cloud
computing systems. The diversity detection and improvement detection operators
are employed by the proposed algorithm to dynamically determine which low-level
heuristic is to be used in finding better candidate solutions. To evaluate the
performance of the proposed method, this study compares the proposed method
with several state-of-the-art scheduling algorithms, by having all of them
implemented on Cloud Sim (a simulator) and Hadoop (a real system). The results
show that HHSA can significantly reduce the make span of task scheduling
compared with the other scheduling algorithms evaluated in this paper, on both
Cloud Sim and Hadoop
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