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| Author | Techniques | Usage | Comments |
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| Kumar Patra et al. [60] | Non-cooperative and cooperative game model | Scheduling framework for a real-time task using game theory concept | The result showed a cooperative game model for task scheduling performs better than a non-cooperative game model. The total completion time and total waiting time in a cooperative game model are less than in the non-cooperative game model |
| Ni et al. [41] | Used a three-layer scheduling model based on whale-Gaussian cloud/whale optimization strategy based on the Gaussian cloud model (GCWOAS2) | It is used for multiobjective task scheduling in cloud computing that is to minimize the completion time of the task via effectively utilizing the virtual machine resources and to keep the load balancing of each virtual machine, reducing the operating cost of the system | |
| Jafar Ababneh [42] | Used a hybrid multiobjective approach called hybrid grey wolf and whale optimization (HGWWO) algorithms that integrates two algorithms, namely, the grey wolf optimizer (GWO) and the whale optimization algorithm (WOA) | A superior level by comparison to the original algorithms GWO and WOA on their own with regard to costs, energy consumption, makespan, use of resources, and degree of imbalance | Implications of cloud scheduling are the planning of tasks on virtual machines and the attenuation of performance |
| Aggarwal et al. [43] | Fruit fly optimization (IFFO) algorithm | To minimize makespan and cost for scheduling multiple workflows in the cloud computing environment | Multiobjective workflow scheduling with scientific standards to optimize QoS parameters is a challenging task |
| Jia et al. [44] | Improved whale optimization algorithm, referred to as IWC | Use the inertial weight strategy for the whale optimization algorithm to improve the local search ability and effectively prevent the algorithm from reaching premature convergence | IWC algorithm has good results in terms of task scheduling time, scheduling cost, and virtual machine |
| Gawali and Shinde [65] | They proposed a heuristic approach that combines the modified analytic hierarchy process (MAHP), bandwidth aware divisible scheduling (BATS) + BAR optimization, longest expected processing time preemption (LEPT), and divide-and-conquer methods to perform task scheduling and resource allocation | Bipartite graphs are utilized to map tasks to appropriate virtual machines | Cybershake scientific workflow and the epigenomics scientific workflow for scheduling algorithm |
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