Associate multi-task scheduling algorithm based on self-adaptive inertia weight particle swarm optimization with disruption operator and chaos operator in cloud environment

1Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

You may have access to this PDF.

Abstract

Random search-based scheduling algorithms, such as particle swarm optimization (PSO), are often used to solve independent multi-task scheduling problems in cloud, but the quality of optimal solution of the algorithm often has greater deviation and poor stability when the tasks are associate. In this paper, we propose an algorithm called SADCPSO to solve this challenging problem, which improves the PSO algorithm by uniquely integrating the self-adaptive inertia weight, disruption operator and chaos operator. In particular, the self-adaptive inertia weight is adopted to adjust the convergence rate, the disruption operator is applied to prevent the loss of population diversity, and the chaos operator is introduced to prevent the solution from tending to jump into the local optimal. Furthermore, we also provide a scheme to apply the SADCPSO algorithm to solve the associate multi-task scheduling problem. In the simulation experiments, we initialize two associate multi-task scheduling examples and take the minimum execution time as our optimization objective. The simulation results demonstrate that the optimal solution of our proposed algorithm has better quality and stability than the baseline PSO algorithm.

Cite

CITATION STYLE

APA

Zhang, R., Tian, F., Ren, X., Chen, Y., Chao, K., Zhao, R., … Wang, W. (2018). Associate multi-task scheduling algorithm based on self-adaptive inertia weight particle swarm optimization with disruption operator and chaos operator in cloud environment. Service Oriented Computing and Applications, 12(2), 87–94. https://doi.org/10.1007/s11761-018-0231-7

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free