Research Area: Cloud Computing
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 CloudSim (a simulator) and Hadoop (a real system). The results show that HHSA can significantly reduce the makespan of task scheduling compared with the other scheduling algorithms evaluated in this paper, on both CloudSim and Hadoop.
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Author(s) Name: Chun-Wei Tsai; Wei-Cheng Huang; Meng-Hsiu Chiang; Ming-Chao Chiang and Chu-Sing Yang
Journal name: IEEE Transactions on Cloud Computing
Conferrence name:
Publisher name: IEEE
DOI: 10.1109/TCC.2014.2315797
Volume Information: Volume: 2, Issue: 2, April-June 1 2014,Page(s): 236 - 250
