Survey on Task Scheduling in Inter-Cloud Environment

Tang Xuhao; Liu Fagui; Wang Bin; Li Chao; Jiang Jun; Tang Quan; Chen Weiming; He Fengwen

doi:10.7544/issn1000-1239.202220021

Journal of Computer Research and Development > 2023 > 60(6): 1262-1275. > DOI: 10.7544/issn1000-1239.202220021 CSTR: 32373.14.issn1000-1239.202220021

Tang Xuhao, Liu Fagui, Wang Bin, Li Chao, Jiang Jun, Tang Quan, Chen Weiming, He Fengwen. Survey on Task Scheduling in Inter-Cloud Environment[J]. Journal of Computer Research and Development, 2023, 60(6): 1262-1275. DOI: 10.7544/issn1000-1239.202220021

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Survey on Task Scheduling in Inter-Cloud Environment

Tang Xuhao^1,,
Liu Fagui^{1, 2, ,},
Wang Bin^2,,
Li Chao^1,,
Jiang Jun^1,,
Tang Quan¹,
Chen Weiming^3,,
He Fengwen^3,

1.
School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006
2.
Peng Cheng Laboratory, Shenzhen, Guangdong 518000
3.
Guangdong Provincial Tax Service, State Taxation Administration, Guangzhou 510627

Funds: This work was supported by the Guangdong Major Project of Basic and Applied Basic Research (2019B030302002), the Science and Technology Project of Guangdong Province (2021B1111600001), the Guangzhou Major Fields Research and Development Program (202007030006), the Guangzhou "China Manufacturing 2025" Industrial Development Funds Program (x2jsD8183470), and the Guangdong Engineering and Technology Research Center Construction Program (GDDST[2016]176).

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Author Bio:
Tang Xuhao: born in 1996. PhD candidate. Student member of CCF. His main research interests include cloud computing and Internet of things

Liu Fagui: born in 1963. PhD, professor, PhD supervisor. Member of CCF. Her main research interests include cloud computing, big data, and Internet of things

Wang Bin: born in 1993. PhD, assistant research fellow. Member of CCF. His main research interests include cloud computing, edge computing, and energy-efficient scheduling. （wangb02@pcl.ac.cn）

Li Chao: born in 1993. PhD candidate. His main research interests include edge computing and reinforcement learning. （cs_lichao@mail.scut.edu.cn）

Jiang Jun: born in 1994. PhD candidate. His main research interests include machine learning, cloud computing, data stream classification, and fuzzy system. （csjun.jiang@mail.scut.edu.cn）

Tang Quan: born in 1997. PhD candidate. His main research interests include computer vision and deep learning

Chen Weiming: born in 1964. Bachelor. His main research interest includes cloud computing. （atiuer@163.com）

He Fengwen: born in 1980. Master. Her main research interest includes cloud computing. （moshefengwen@163.com）
Received Date: January 03, 2022
Revised Date: June 22, 2022
Available Online: February 26, 2023

Graphical Abstract

Abstract

Abstract

As cloud computing technology advances continuously, there are a growing number of enterprises and organizations choosing the inter-cloud approach to apply on IT delivery. Inter-cloud environments can efficiently solve problems such as low resource utilization, resource limitation, and vendor lock-in in traditional single-cloud environments, and manage cloud resources in an integrated model. Due to the heterogeneity of resources in the inter-cloud environment, which will complicate the scheduling of inter-cloud tasks. Based on the current status, how to logically schedule user tasks and allocate them to the most suitable inter-cloud resources for execution has developed to be an important issue to be solved in the inter-cloud environment. From the perspective of the inter-cloud environment, we discuss the progress and future challenges of research on the task of scheduling algorithms under this environment. Firstly, combined with the characteristics of an inter-cloud environment, cloud computing is divided into federated cloud and multi-cloud environments and introduced in detail. Meanwhile, the existing task scheduling types are reviewed and their advantages and disadvantages are analyzed. Secondly, based on the classification and current research procedure, representative documents are selected to analyze the algorithms for task scheduling on inter-cloud. Finally, shortcomings in research on algorithms for task scheduling in inter-cloud and future research trends are discussed, which provide a reference for further research on inter-cloud task scheduling.
- cloud computing,
- inter-cloud,
- task scheduling,
- federated cloud,
- multi-cloud

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References (71)

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