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Improved Particle Swarm Optimization Based Workflow Scheduling in Cloud-Fog Environment

  • Rongbin Xu
  • Yeguo Wang
  • Yongliang Cheng
  • Yuanwei Zhu
  • Ying XieEmail author
  • Abubakar Sadiq Sani
  • Dong Yuan
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 342)

Abstract

Mobile edge devices with high requirements typically need to obtain faster response on local network services. Fog computing is an emerging computing paradigm motivated by this need, which currently is viewed as an extension of cloud computing. This computing paradigm is presented to provide low commutation latency service for workflow applications. However, how to schedule workflow applications for seeking the tradeoff between makespan and cost in cloud-fog environment is facing huge challenge. To address this issue, in current paper, we propose a workflow scheduling algorithm based on improved particle swarm optimization (IPSO), where a nonlinear decreasing function of inertia weight in PSO is designed for promoting PSO to gain the optimal solution. Finally, comprehensive simulation experiment results show that our proposed scheduling algorithm is more cost-effective and can obtain better performance than baseline approach.

Keywords

Cloud computing Fog computing Workflow scheduling PSO 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rongbin Xu
    • 1
    • 2
  • Yeguo Wang
    • 1
  • Yongliang Cheng
    • 1
  • Yuanwei Zhu
    • 1
  • Ying Xie
    • 1
    • 2
    Email author
  • Abubakar Sadiq Sani
    • 3
  • Dong Yuan
    • 3
  1. 1.School of Computer Science and TechnologyAnhui UniversityHefeiChina
  2. 2.Co-Innovation Center for Information Supply and Assurance TechnologyAnhui UniversityHefeiChina
  3. 3.School of Electrical and Information EngineeringUniversity of SydneySydneyAustralia

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