{"title":"Makespan and Security-Aware Workflow Scheduling for Cloud Service Cost Minimization","authors":"Liying Li;Chengliang Zhou;Peijin Cong;Yufan Shen;Junlong Zhou;Tongquan Wei","doi":"10.1109/TCC.2024.3382351","DOIUrl":null,"url":null,"abstract":"The market penetration of Infrastructure-as-a-Service (IaaS) in cloud computing is increasing benefiting from its flexibility and scalability. One of the most important issues for IaaS cloud service providers is to minimize the monetary cost while meeting cloud user experience requirements such as makespan and security. Prior works on cloud service cost minimization ignore either security or makespan which is very important for user experience. In this article, we propose a two-stage algorithm to solve the cloud service cost minimization problem at the premise of satisfying the security and makespan requirements of cloud users. Specifically, in the first stage, we propose a novel security service selection scheme to ensure system security by judiciously selecting security services with low cost for tasks under the constraints of time and security. In the second stage, to further reduce the cloud service cost, we design a workflow scheduling method based on an improved firefly algorithm (IFA). The IFA-based method schedules cloud service workflows to virtual machines of small cost at the premise of guaranteeing security and makespan. It can quickly find the workflow scheduling solution with minimized cost using our designed updating scheme and mapping operator. Extensive simulations are conducted on real-world workflows to verify the efficacy of the proposed two-stage method. Simulation results show that the proposed two-stage method outperforms the baseline and two benchmarking methods in terms of cost minimization without violating security and time constraints. Compared to benchmarking methods, the cloud service cost can be reduced by up to 57.6% by using our proposed approach.","PeriodicalId":13202,"journal":{"name":"IEEE Transactions on Cloud Computing","volume":"12 2","pages":"609-624"},"PeriodicalIF":5.3000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cloud Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10480637/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The market penetration of Infrastructure-as-a-Service (IaaS) in cloud computing is increasing benefiting from its flexibility and scalability. One of the most important issues for IaaS cloud service providers is to minimize the monetary cost while meeting cloud user experience requirements such as makespan and security. Prior works on cloud service cost minimization ignore either security or makespan which is very important for user experience. In this article, we propose a two-stage algorithm to solve the cloud service cost minimization problem at the premise of satisfying the security and makespan requirements of cloud users. Specifically, in the first stage, we propose a novel security service selection scheme to ensure system security by judiciously selecting security services with low cost for tasks under the constraints of time and security. In the second stage, to further reduce the cloud service cost, we design a workflow scheduling method based on an improved firefly algorithm (IFA). The IFA-based method schedules cloud service workflows to virtual machines of small cost at the premise of guaranteeing security and makespan. It can quickly find the workflow scheduling solution with minimized cost using our designed updating scheme and mapping operator. Extensive simulations are conducted on real-world workflows to verify the efficacy of the proposed two-stage method. Simulation results show that the proposed two-stage method outperforms the baseline and two benchmarking methods in terms of cost minimization without violating security and time constraints. Compared to benchmarking methods, the cloud service cost can be reduced by up to 57.6% by using our proposed approach.
期刊介绍:
The IEEE Transactions on Cloud Computing (TCC) is dedicated to the multidisciplinary field of cloud computing. It is committed to the publication of articles that present innovative research ideas, application results, and case studies in cloud computing, focusing on key technical issues related to theory, algorithms, systems, applications, and performance.