Research Area: Cloud Computing
Workflow scheduling is one of the burning topics that has drawn enormous attention recently in the research community of cloud computing due to its wide applications in astronomy, physics, bioinformatics, health care and so on. This is a well-known NP-complete problem. It presents an interesting aspect of achieving minimum processing time of all the tasks and maximum resource utilization in cloud resources. Therefore, many algorithms have been developed for workflow scheduling. However, most of them consider a static priority of the tasks which is non-realistic for heterogeneous cloud computing environment. In this paper, we propose a workflow scheduling algorithm which considers dynamic priority of the tasks. The algorithm undergoes a process of min–max normalization followed by the calculation of the dynamic threshold to dispatch the tasks into one of the virtual machines. The algorithm is extensively simulated using various benchmark, scientific and real-life workflows. All the simulated results are compared with other four existing workflow scheduling algorithms. The simulated results confirm that the proposed algorithm lags behind all the four existing algorithms in terms of makespan and average cloud resource utilization. The simulation results are also validated through analysis of variance statistical test.
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Author(s) Name: Indrajeet Gupta, Madhu Sudan Kumar & Prasanta K. Jana
Journal name: Arabian Journal for Science and Engineering
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Publisher name: Springer
DOI: 10.1007/s13369-018-3261-8
Volume Information: volume 43, pages 7945–7960 (2018)
