Article: Cloud workflow scheduling algorithm based on multi-objective particle swarm optimisation Journal: International Journal of Grid and Utility Computing (IJGUC) 2023 Vol.14 No.6 pp.583 - 596 Abstract: Owing to the characteristics of market-oriented cloud computing, the objective function of cloud workflow scheduling algorithm should not only consider the running time, but also consider the running costs. The nature of cloud workflow scheduling is to map each task of a workflow instance to appropriate computing resources. Owing to the existence of temporal dependencies and causal dependencies between tasks, the scheduling of cloud workflow instance becomes more complex. The main contribution of this paper is to propose a cloud workflow scheduling algorithm based on multi-objective particle swarm optimisation. The algorithm takes makespan and total cost as two objectives. It provides users with a set of Pareto optimal solutions to select an optimal scheduling scheme according to their own preferences. The performance of our algorithm is compared with state-of-the-art multi-objective meta-heuristics and classical single-objective scheduling algorithm. The simulation results show that our solution delivers better convergence and optimisation capability as compared to others. Hence, it is applicable to solve multi-objective optimisation problems for scheduling workflows over cloud platform. Inderscience Publishers - linking academia, business and industry through research

Title: Cloud workflow scheduling algorithm based on multi-objective particle swarm optimisation

Authors: Hongfeng Yin; Baomin Xu; Weijing Li

Addresses: School of Computer and Information Technology, Cangzhou Jiaotong College, Cangzhou, Hebei, China ' School of Computer and Information Technology, Beijing Jiaotong University, Haidian District, Beijing, China ' School of Computer and Information Technology, Cangzhou Jiaotong College, Cangzhou, Hebei, China

Abstract: Owing to the characteristics of market-oriented cloud computing, the objective function of cloud workflow scheduling algorithm should not only consider the running time, but also consider the running costs. The nature of cloud workflow scheduling is to map each task of a workflow instance to appropriate computing resources. Owing to the existence of temporal dependencies and causal dependencies between tasks, the scheduling of cloud workflow instance becomes more complex. The main contribution of this paper is to propose a cloud workflow scheduling algorithm based on multi-objective particle swarm optimisation. The algorithm takes makespan and total cost as two objectives. It provides users with a set of Pareto optimal solutions to select an optimal scheduling scheme according to their own preferences. The performance of our algorithm is compared with state-of-the-art multi-objective meta-heuristics and classical single-objective scheduling algorithm. The simulation results show that our solution delivers better convergence and optimisation capability as compared to others. Hence, it is applicable to solve multi-objective optimisation problems for scheduling workflows over cloud platform.

Keywords: multi-objective optimisation; cloud computing; particle swarm optimisation; workflow scheduling.

DOI: 10.1504/IJGUC.2023.135304

International Journal of Grid and Utility Computing, 2023 Vol.14 No.6, pp.583 - 596

Received: 15 Feb 2021
Accepted: 27 Nov 2021
Published online: 05 Dec 2023 *

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Title: Cloud workflow scheduling algorithm based on multi-objective particle swarm optimisation

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