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Efficient budget aware workflow scheduling in cloud using adaptive Tasmanian Devil Optimization algorithm
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DOI：10.1007/s11042-023-17088-w.png)
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Abstract
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In order to decrease energy usage in cloud computing, we design the Efficient Budget aware Workflow Scheduling Algorithm (EBWSM) in this study. To achieve this concept, an adaptive Tasmanian Devil Optimization algorithm (ATDO) is developed. The projected ATDO is a combination of Tasmanian Devil Optimization (TDO) and Levy Flight (LF) functions. In the TDO, the position updating process is updated with the assistance of the LF function. The objective function of the cost coefficient factor and energy function is considered for enabling the efficient workflow scheduling model in cloud computing. The efficient pre-suggestion of the available budget is a main key process of this projected method. This workflow scheduling method was created as an effective way to reduce energy consumption while taking the cost coefficient factor and energy into account. This enables equitable allocation of the supplied budget for the cloud workflow application's unscheduled jobs.The proposed method is implemented and compared with the conventional methods of workflow scheduling model. In terms of energy usage, cost function, and makespan, the projected method outperformed the current approaches.
Keywords:
Budget constraints
Workflow scheduling algorithm
Energy function
Cost coefficient factor
Tasmanian devil optimization
Levy flight
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