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Game strategies among multiple cloud computing platforms for non-cooperative competing assignment user tasks

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Abstract

With the development of cloud computing technology, more and more cloud computing platforms are emerging which provide a great deal of computing services. But every cloud computing platform is selfish, there are many competitions and contradictions among them. Only if many cloud computing platforms are united and cooperative, they can realize resource sharing and aggregate a greater capacity. Therefore, this paper studies game strategies among multiple cloud computing platforms for coordinating and competing assignment user tasks. Firstly, we present a framework of federated cloud computing platforms, which is composed of multiple private clouds. User tasks will be received, assigned, and executed by the federated cloud. Secondly, a non-cooperative game model for tasks allocation is established among multiple private clouds. Then, the Nash equilibrium solution under the non-cooperative game is transformed into a function optimization problem. We use the particle swarm optimization algorithm to obtain near optimal solution. Finally, based on the Nash equilibrium solution, we propose a tasks allocation algorithm called NGTA for multiple private clouds in the non-cooperative game. The experimental results show that in the presence of competition, compared with Max–Min and Min-Min algorithm, NGTA algorithm can bring balanced utility satisfaction to each private cloud. The expected utility deviation of each private cloud is very small, the average is about 0.002.

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Acknowledgements

This work was supported by the National Key R&D Program of China under grant No. 2020YFD1100605, 2019YFB1704100; the National Social Science Foundation of China under grant No. 17BQT086; the National Nature Science Foundation of China under grant No. 61762048;the Subproject of National Seafloor Observatory System of China under grant No. 2970000001/001/016;Key scientific and technological research projects of Jiangxi Provincial Department of Education under grant No. GJJ190180,GJJ200428; Scientific research fund of Jiangxi Agricultural University under grant No. 9232307210.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Tongji University, Shanghai, 200092, China

    Guosun Zeng

  2. Software College, Jiangxi Agricultural University, Nanchang, 330045, China

    Huanliang Xiong & Canghai Wu

  3. School of Chemical Science and Engineering, Tongji University, Shanghai, 200092, China

    Chunling Ding

  4. School of Science and Information Science, Qingdao Agricultural University, Qingdao, 266109, Shandong, China

    Guijuan Kuang

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  1. Guosun Zeng
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  2. Huanliang Xiong
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  3. Chunling Ding
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  4. Guijuan Kuang
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  5. Canghai Wu
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Contributions

The authors and their attributions: GuoSun Zeng and Huanliang Xiong designed research, Chunling Ding and GuiJuan Kuang performed research, Huanliang Xiong and Canghai Wu analyzed data and wrote the paper.

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Correspondence to Huanliang Xiong.

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The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

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Written informed consent for publication of this paper was obtained from the Tongji University, Jiangxi Agricultural University, Qingdao Agricultural University and all authors.

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Zeng, G., Xiong, H., Ding, C. et al. Game strategies among multiple cloud computing platforms for non-cooperative competing assignment user tasks. J Supercomput 78, 14317–14342 (2022). https://doi.org/10.1007/s11227-022-04437-z

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