Scientific Workflow Makespan Minimization in Edge Multiple Service Providers Environment |
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Authors: | Bukhari S Sabahat H Younus Muhammad Usman Jaffri Zain ul Abidin Arshad Shehzad Hassan Muhammad Rizwan Anjum Muhammad Narejo Sanam |
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Affiliation: | 1.College of Computer Science, Neijiang Normal University, Neijiang, 641100, People’s Republic of China ;2.Ecole Mathématiques, Informatique, Télécommunications de Toulouse, Université de Toulouse, Toulouse, France ;3.Department of Computer Science & IT, University of Jhang, Jhang, Pakistan ;4.College of Physics and Electronic Information Engineering, Neijiang Normal University, Neijiang, 641100, People’s Republic of China ;5.Department of Engineering Technology, The University of Faisalabad, Faisalabad, 38000, Pakistan ;6.Department of Electronic Engineering, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan ;7.Department of Computer Systems Engineering, Mehran University of Engineering & Technology (MUET), Jamshoro, Pakistan ; |
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Abstract: | The edge computing model offers an ultimate platform to support scientific and real-time workflow-based applications over the edge of the network. However, scientific workflow scheduling and execution still facing challenges such as response time management and latency time. This leads to deal with the acquisition delay of servers, deployed at the edge of a network and reduces the overall completion time of workflow. Previous studies show that existing scheduling methods consider the static performance of the server and ignore the impact of resource acquisition delay when scheduling workflow tasks. Our proposed method presented a meta-heuristic algorithm to schedule the scientific workflow and minimize the overall completion time by properly managing the acquisition and transmission delays. We carry out extensive experiments and evaluations based on commercial clouds and various scientific workflow templates. The proposed method has approximately 7.7% better performance than the baseline algorithms, particularly in overall deadline constraint that gives a success rate. |
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