Research Area:  Cloud Computing

Abstract:

The last decades have seen a considerable progress on workflow scheduling in heterogeneous computing environments. However, existing methods still need to be improved on the performance in the makespan-based metrics. This paper proposes a novel workflow scheduling algorithm named Greedy-Ant to minimize total execution time of an application in heterogeneous environments. First, the ant colony system is applied to scheduling from a new standpoint by guiding ants to explore task priorities and simultaneously assign tasks to machines. Second, forward/backward dependence is defined to indicate the global significance of each node, based on which, a new heuristic factor is proposed to help ants search for task sequences. Finally, a greedy machine allocating strategy is presented. Experimental results demonstrate that Greedy-Ant outperforms the state of the art up to 18% in the metric of speedup.

Keywords:  

Author(s) Name:  Bin Xiang; Bibo Zhang; Lin Zhang

Publisher name:  IEEE

DOI:  10.1109/ACCESS.2017.2715279

Volume Information:  Volume: 5, Page(s): 11404 - 11412

Paper Link:   https://ieeexplore.ieee.org/abstract/document/7954970