Makespan and Security-Aware Workflow Scheduling for Cloud Service Cost Minimization

被引:16
作者
Li, Liying [1 ,2 ]
Zhou, Chengliang [1 ]
Cong, Peijin [1 ]
Shen, Yufan [1 ]
Zhou, Junlong [1 ,3 ]
Wei, Tongquan [4 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Nanjing 210094, Peoples R China
[2] East China Normal Univ, Engn Res Ctr Software Hardware Codesign Technol &, Minist Educ, Shanghai 200062, Peoples R China
[3] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 211111, Peoples R China
[4] East China Normal Univ, Sch Comp Sci & Technol, Shanghai 200062, Peoples R China
基金
中国国家自然科学基金;
关键词
Cloud computing; Security; Costs; Task analysis; Scheduling; Minimization; Processor scheduling; cost minimization; makespan and security; workflow scheduling; OPTIMIZATION;
D O I
10.1109/TCC.2024.3382351
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:609 / 624
页数:16
相关论文
共 33 条
[1]   Deadline-constrained workflow scheduling algorithms for Infrastructure as a Service Clouds [J].
Abrishami, Saeid ;
Naghibzadeh, Mahmoud ;
Epema, Dick H. J. .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2013, 29 (01) :158-169
[2]   Multi-objective scheduling strategy for scientific workflows in cloud environment: A Firefly-based approach [J].
Adhikari, Mainak ;
Amgoth, Tarachand ;
Srirama, Satish Narayana .
APPLIED SOFT COMPUTING, 2020, 93
[3]  
Amazon, 2024, Amazon EC2 pricing
[4]   Modified firefly algorithm for workflow scheduling in cloud-edge environment [J].
Bacanin, Nebojsa ;
Zivkovic, Miodrag ;
Bezdan, Timea ;
Venkatachalam, K. ;
Abouhawwash, Mohamed .
NEURAL COMPUTING & APPLICATIONS, 2022, 34 (11) :9043-9068
[5]   Applying a Consumer-Centric Framework for Trust Assessment of Cloud Computing Service Providers [J].
Balcao-Filho, Amandio ;
Ruiz, Natasha ;
Rosa, Ferrucio de Franco ;
Bonacin, Rodrigo ;
Jino, Mario .
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 16 (01) :95-107
[6]  
Bharathi S, 2008, 2008 THIRD WORKSHOP ON WORKFLOWS IN SUPPORT OF LARGE-SCALE SCIENCE (WORKS 2008), P11
[7]   A balanced scheduler with data reuse and replication for scientific workflows in cloud computing systems [J].
Casas, Israel ;
Taheri, Javid ;
Ranjan, Rajiv ;
Wang, Lizhe ;
Zomaya, Albert Y. .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2017, 74 :168-178
[8]   Scheduling for Workflows with Security-Sensitive Intermediate Data by Selective Tasks Duplication in Clouds [J].
Chen, Huangke ;
Zhu, Xiaomin ;
Qiu, Dishan ;
Liu, Ling ;
Du, Zhihui .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2017, 28 (09) :2674-2688
[9]   Customer Adaptive Resource Provisioning for Long-Term Cloud Profit Maximization under Constrained Budget [J].
Cong, Peijin ;
Zhang, Zhixing ;
Zhou, Junlong ;
Liu, Xin ;
Liu, Yao ;
Wei, Tongquan .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2022, 33 (06) :1373-1392
[10]   A Reinforcement Learning-Based Mixed Job Scheduler Scheme for Grid or IaaS Cloud [J].
Cui, Delong ;
Peng, Zhiping ;
Xiong, Jianbin ;
Xu, Bo ;
Lin, Weiwei .
IEEE TRANSACTIONS ON CLOUD COMPUTING, 2020, 8 (04) :1030-1039