AILS: A budget-constrained adaptive iterated local search for workflow scheduling in cloud environment
作者：
Highlights：
• An AILS framework was proposed for budget constrained cloud workflow scheduling problem.
• A perturbation mechanism was designed to control the resource pool and task permutation.
• The intensification strategy was employed to assign the tasks to the leased resources.
• The Markov chain was employed to analyze the convergence of AILS.
• The well-known scientific workflows were utilized to evaluate the performance of AILS.
摘要
•An AILS framework was proposed for budget constrained cloud workflow scheduling problem.•A perturbation mechanism was designed to control the resource pool and task permutation.•The intensification strategy was employed to assign the tasks to the leased resources.•The Markov chain was employed to analyze the convergence of AILS.•The well-known scientific workflows were utilized to evaluate the performance of AILS.
论文关键词：Cloud computing,Workflow scheduling,Budget constraint,Iterated local search,Markov model
论文评审过程：Received 19 February 2021, Revised 27 December 2021, Accepted 2 March 2022, Available online 18 March 2022, Version of Record 24 March 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.116824
