Supervised Learning Based Truthful Auction Mechanism Design in Cloud Computing

Jixian ZHANG; Ning XIE; Xuejie ZHANG; Weidong LI

doi:10.11999/JEIT180587

Volume 41 Issue 5

Apr. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(5): 1243-1250

Jixian ZHANG, Ning XIE, Xuejie ZHANG, Weidong LI. Supervised Learning Based Truthful Auction Mechanism Design in Cloud Computing[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1243-1250. doi: 10.11999/JEIT180587

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Jixian ZHANG, Ning XIE, Xuejie ZHANG, Weidong LI. Supervised Learning Based Truthful Auction Mechanism Design in Cloud Computing[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1243-1250. doi: 10.11999/JEIT180587

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Supervised Learning Based Truthful Auction Mechanism Design in Cloud Computing

doi: 10.11999/JEIT180587

1.
School of Information Science and Engineering, Yunnan University, Kunming 650500, China
2.
School of Mathematics and Statistics, Yunnan University, Kunming 650500, China

Funds: The National Natural Science Foundation of China (61472345, 61762091, 11663007), The Scientific Research Foundation of Department of Education of Yunnan Province (2017ZZX228)

Received Date: 2018-06-13
Rev Recd Date: 2018-12-24

Available Online: 2019-01-02

Publish Date: 2019-05-01

Abstract

Abstract

Auction based resource allocation can make resource provider get more profit, which is a major challenging problem for cloud computing. However, the resource allocation problem is NP-hard and can not be solved in polynomial time. Existing studies mainly use approximate algorithms or heuristic algorithms to implement resource allocation in auction, but these algorithms have the disadvantages of low computational efficiency or low allocate accuracy. In this paper, the classification and regression of supervised learning is used to model and analyze multi-dimensional cloud resource allocation, for the different scale of problem, three resource allocation predict algorithms based on linear regression, logistic regression and Support Vector Machine (SVM) are proposed. Through the learning of the small-scale training set, the predict model can guarantee that the social welfare, allocation accuracy, and resource utilization in the feasible solution are very close to the optimal allocation solution. The payment price algorithm based on the critical value theory is proposed which ensure the truthful property of the auction mechanism design. Final experimental results show that the proposed scheme has good effect for resource allocation in cloud computing.
- Cloud computing,
- Resource allocation,
- Mechanism design,
- Supervised learning

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References(17)

References

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