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A Heterogeneous Multiprocessor Independent Task Scheduling Algorithm Based on Improved PSO

  • Xiaohui Cheng
  • Fei DaiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 895)

Abstract

The independent task scheduling problem of heterogeneous multi-processors belongs to the NP-hard problem. The emergence of evolutionary algorithms provides a new idea for solving this problem. Particle swarm optimization (PSO) is a kind of intelligent evolutionary algorithm and it could be used to solve scheduling problem. We firstly discretized the representation of particle swarm optimization algorithm and made it suitable for the scheduling problem of heterogeneous multiprocessors. Then, the PSO algorithm was introduced into heterogeneous multiprocessors independent task scheduling problem by modeling method. In order to overcome particle swarm optimization algorithm’s problem that is easy to fall into local optimum and premature convergence. We proposed a heterogeneous multiprocessor independent task scheduling algorithm based on improved PSO by improving the update operation of particle swarm optimization algorithm and transformed it into crossover and mutation operation of genetic algorithm. The experimental results show that the improved PSO scheduling algorithm can overcome the premature defects of PSO algorithm and the makespan of proposed IPSO is smaller than PSO.

Keywords

Task scheduling Independent tasks Particle swarm optimization Heterogeneous multiprocessors 

Notes

Acknowledgments

As the research of the thesis is sponsored by National Natural Science Foundation of China (No: 61662017, No: 61262075), Key R & D projects of Guangxi Science and Technology Program (AB17195042), Guangxi Science and Technology Development Special Science and Technology Major Project (No: AA18118009), Guangxi Key Laboratory Fund of Embedded Technology and Intelligent System, we would like to extend our sincere gratitude to them.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Guangxi Key Laboratory of Embedded Technology and Intelligent System, College of Information Science and EngineeringGuilin University of TechnologyGuilinChina

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