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Cloud computing task scheduling algorithm based on two-stage adaptive search

Sun Chaoli1a
Zhang Aolong1a
Liu Xiaotong1b
Que Lingyan2
Zhao Zhicheng3
1. a. School of Computer Science & Technology, b. School of Electronic Information Engineering, Taiyuan University of Science & Technology, Taiyuan 030024, China
2. Dispatch Control Center, State Grid Zhejiang Electric Power Company, Ltd. , Hangzhou 310007, China
3. Dept. of Automation, Taiyuan Institute of Technology, Taiyuan 030024, China

Abstract

Aiming at the escalating conflicts between user demands and cloud service providers' interests in task scheduling, along with the challenges of multi-objective trade-offs, this paper presented a task scheduling model that integrates the preferences of both users and cloud service providers, and proposed a two-stage adaptive search-based cloud computing task scheduling algorithm (TSASA) to solve this model. In the first stage, the algorithm employed preference-aware distance measurement to guide population aggregation. Upon detecting that population centroid variance met predefined thresholds, it activated a preference region classification strategy to conduct second-stage exploration. Compared to classical multi-objective algorithms, scheduling domain heuristic algorithms, and the latest cloud computing scheduling methods, the experimental results demonstrated that the proposed algorithm achieved a completion time approximately 29% shorter than NSGA-III and a leasing cost about 37.5% lower than RVEA in a medium-scale cloud environment. In a large-scale cloud environment, the energy consumption was reduced by approximately 28.2% compared to GrEA, and the load balance index was about 34.8% lower than MCT-PSO. The experimental results verify the effectiveness of the proposed algorithm in balancing the interests of multiple parties and achieving multi-objective collaborative optimization, providing a new idea for task scheduling in complex cloud environments.

Foundation Support

国家自然科学基金面上项目(62372319)
山西省重点研发计划项目(202102020101002,202202010101002)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.01.0013
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 8

Publish History

[2025-04-02] Accepted Paper

Cite This Article

孙超利, 张澳龙, 刘晓彤, 等. 一种基于两阶段自适应搜索的云计算任务调度算法 [J]. 计算机应用研究, 2025, 42 (8). (2025-04-17). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0013. (Sun Chaoli, Zhang Aolong, Liu Xiaotong, et al. Cloud computing task scheduling algorithm based on two-stage adaptive search [J]. Application Research of Computers, 2025, 42 (8). (2025-04-17). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0013. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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