Survey on Task Scheduling in Inter-Cloud Environment

被引:0
作者
Tang X. [1 ]
Liu F. [1 ,2 ]
Wang B. [2 ]
Li C. [1 ]
Jiang J. [1 ]
Tang Q. [1 ]
Chen W. [3 ]
He F. [3 ]
机构
[1] School of Computer Science and Engineering, South China University of Technology, Guangzhou
[2] Peng Cheng Laboratory, Guangdong, Shenzhen
[3] Guangdong Provincial Tax Service, State Taxation Administration, Guangzhou
来源
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | 2023年 / 60卷 / 06期
关键词
cloud computing; federated cloud; inter-cloud; multi-cloud; task scheduling;
D O I
10.7544/issn1000-1239.202220021
中图分类号
学科分类号
摘要
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. © 2023 Science Press. All rights reserved.
引用
收藏
页码:1262 / 1275
页数:13
相关论文
共 71 条
[21]  
Zhuojing Tian, Zhenchun Huang, Yinong Zhang, Review of task scheduling methods in cloud computing environment[J], Computer Engineering and Applications, 57, 2, (2021)
[22]  
Xiaojin Ma, Guobin Rao, Huahu Xu, Research on task scheduling in cloud computing[J], Computer Science, 46, 3, (2019)
[23]  
Marmol F G, Perez G M., Towards pre-standardization of trust and reputation models for distributed and heterogeneous systems[J], Computer Standards & Interfaces, 32, 4, pp. 185-196, (2010)
[24]  
Haiyang Hu, Runhua Liu, Hua Hu, Multi-objective optimization for task scheduling in mobile cloud computing[J], Journal of Computer Research and Development, 54, 9, (2017)
[25]  
Wang Yawen, Guo Yunfei, Liu Wenyan, Et al., A task scheduling method for cloud workflow security[J], Journal of Computer Research and Development, 55, 6, pp. 66-75, (2018)
[26]  
Liu Juefu, Liu Peng, The research of load imbalance based on min-min in grid, Proc of 2010 Int Conf on Computer Design and Applications, (2010)
[27]  
Etminani K, Naghibzadeh M., A min-min max-min selective algorithm for grid task scheduling, Proc of the 3rd IEEE/IFIP Int Conf in Central Asia on Internet, (2007)
[28]  
Dorigo M, Caro G D., Ant colony optimization: A new meta-heuristic[C], Proc of 1999 Congress on Evolutionary Computation, pp. 1470-1477, (1999)
[29]  
Dorigo M, Stutzle T., The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances[M], pp. 250-285, (2003)
[30]  
Bratton D, Kennedy J., Defining a standard for particle swarm optimization[C], Proc of 2007 IEEE Swarm Intelligence Symp, pp. 120-127, (2007)