Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 210800154-6.doi: 10.11896/jsjkx.210800154

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Workflow Scheduling Strategy for Deadline Constrained and Cost Optimization in Cloud

WANG Zi-jian1, LU Zheng-hao1,2, PAN Ji-kui1,2, SUN Fu-quan1   

  1. 1 School of Mathematics and Statistics,Northeastern University at Qinhuangdao,Qinhuangdao,Hebei 066000,China
    2 School of Information Science and Engineering,Northeastern University,Shenyang 110000,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:WANG Zi-jian,born in 1968,master.His main research interest is workflow scheduling.
    SUN Fu-quan,born in 1964,Ph.D,professor.His main research interests include cloud resource scheduling and allocation and big data analysis.
  • Supported by:
    National Key R & D Program of China(2018YFB1402800).

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Abstract: Workflow scheduling in cloud is one of the most challenging issues today.It focuses on executing workflow applications with interdependent tasks mapped to virtual machines under specified quality of service requirements.Cloud service provi-ders offer virtual machines with different performances at different prices.The same workflow with different virtual machines can result in different makespan and cost.One of the main problems of workflow scheduling in cloud is to find a cheaper scheduling method on the premise of meeting the deadline.The proposed deadline constrained cost optimization algorithm for workflow scheduling in cloud DCCO can solve the above problems.It assigns deadlines based on δ-alap and also considers cases where two tasks may be assigned to the same virtual machine.Experiments show that compared with other classical scheduling algorithms,DCCO has the highest success rate under different types of workflow tests,meets the deadline constraint,and can optimize the exe-cution cost.

Key words: Cloud, Workflow scheduling, Deadline, Cost, Optimization

CLC Number: 

  • TP393
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